diff --git a/AMAKFX/README.md b/AMAKFX/README.md
index 9bf1ac1c346140eee3787661c2c3da214377c7b5..4e966b1594a18ffbee697324a727d544130e40e3 100644
--- a/AMAKFX/README.md
+++ b/AMAKFX/README.md
@@ -1,13 +1,28 @@
-# This is the README from the old version of AMAK, some part may be outdated ! #
+# This is a fork of AMAK, now using JavaFX instead of Swing #
[The original repo](https://bitbucket.org/perlesa/amak/overview)
-This repository contains a framework made to facilitate the development of multi-agent system.
-Examples are available in the package fr.irit.smac.amak.examples.
-# [Click here to download the latest standalone version](https://bitbucket.org/perlesa/amak/raw/master/Release/AmakFramework-standalone.jar?at=master) #
+## AMAKFX changes (2019-07-25) :
+These changes were made for a particular project, without much care for backward compatibility. But the overall philosophy should be the same.
-# Recent changes #
+### Possible breaking changes :
++ Anything related with the GUI in Swing.
++ Support for asynchronous agent has been dropped, you may still use then, but no promise are made for the visualization.
+
+### Changes :
++ Build system is now maven.
++ Use JavaFX instead of Swing. JavaFX run on a different thread than the simulation, when updating the GUI from the simulation thread you must be extra careful for :
+ + Running JavaFX code on the JavaFX thread, by only using AMAKFX methods, or by learning how to use JavaFX's RunLater (see AMAKFX's [RunLaterHelper](src/fr/irit/smac/amak/tools/RunLaterHelper.java))
+ + Not overload JavaFX call queue with draw call, leading to unpredictable result. For that purpose a new option has been added to Configuration : waitForGui, default at true. Each simulation cycle, AMAK will wait for JavaFX call queue to be empty. But queue overload can still happen inside a cycle. Symptoms are : long freeze, part of GUI not updating, or becoming white.
++ The VUI has been overhauled, it now provide extra features :
+ + Drawable can detect events, and dispatch these events to linked drawables.
+ + VUI Explorer, a sided bar that show a list of visible Drawable in its VUI. Features : hovering an element in the VUI Explorer highlight it in the VUI. Search for element in the VUI Explorer with regex. Click an element to display additional info (when available).
++ Plotting is now done with JFreeChart, AMAKFX provide an helper class : AmakPlot.
++ Tabs can be drag-n-dropped to rearrange them. Dropping a tab outside the tab bar will open it in a new window (despite the mouse cursor showing it's impossible)
++ Changes on how logging work, the a Log object now accept multiple action. Added the Loggable interface,with default methods, allowing a class to easily log to a file.
+
+# Old AMAK README #
## 1.5.3 (11/28/2018) ##
### New features: none
diff --git a/AMAKFX/pom.xml b/AMAKFX/pom.xml
index 274c8e758e4f45d4215c0374320e7990b9caadfe..7de3815da4c742af6d5a9a738d71bf0a5def69b2 100644
--- a/AMAKFX/pom.xml
+++ b/AMAKFX/pom.xml
@@ -22,11 +22,6 @@
</build>
<dependencies>
- <dependency>
- <groupId>org.junit.jupiter</groupId>
- <artifactId>junit-jupiter-engine</artifactId>
- <version>5.3.1</version>
- </dependency>
<dependency>
<groupId>org.jfree</groupId>
@@ -34,18 +29,6 @@
<version>1.0.1</version>
</dependency>
- <dependency>
- <groupId>org.kordamp.ikonli</groupId>
- <artifactId>ikonli-javafx</artifactId>
- <version>2.4.0</version>
- </dependency>
-
- <dependency>
- <groupId>org.kordamp.ikonli</groupId>
- <artifactId>ikonli-dashicons-pack</artifactId>
- <version>2.4.0</version>
- </dependency>
-
<!-- Local jars dependencies -->
<dependency>
<groupId>agent-messaging</groupId>
diff --git a/AMAKFX/src/fr/irit/smac/amak/Amas.java b/AMAKFX/src/fr/irit/smac/amak/Amas.java
index 93871e169442c7e134e01dda00c686c7667aada8..a73d0e5107ef13fc638c7e17037858d93ae44c5d 100644
--- a/AMAKFX/src/fr/irit/smac/amak/Amas.java
+++ b/AMAKFX/src/fr/irit/smac/amak/Amas.java
@@ -166,7 +166,7 @@ public class Amas<E extends Environment> implements Schedulable {
/**
* Effectively add agent to the system
*/
- protected void addPendingAgents() {
+ public void addPendingAgents() {
// The double loop is required as the method onReady should only be called when
// all the agents have been added
synchronized (agentsPendingAddition) {
diff --git a/AMAKFX/src/fr/irit/smac/amak/Configuration.java b/AMAKFX/src/fr/irit/smac/amak/Configuration.java
index fd9eb44a8e21212a4b7340c2669e75291f57f451..bc8050f8b87e296f7497acf1932764c02508c4f2 100644
--- a/AMAKFX/src/fr/irit/smac/amak/Configuration.java
+++ b/AMAKFX/src/fr/irit/smac/amak/Configuration.java
@@ -1,44 +1,50 @@
-package fr.irit.smac.amak;
-
-import fr.irit.smac.amak.Amas.ExecutionPolicy;
-
-/**
- * This class is used to define global configuration BEFORE calling any other
- * classes/methods of the framework.
- *
- * @author Alexandre Perles
- *
- */
-public class Configuration {
- /**
- * The maximal number of threads that can be executed simultaneously
- */
- public static int allowedSimultaneousAgentsExecution = 1;
- /**
- * The execution policy refers to the synchronization between agents execution.
- * ONE_PHASE means that agents can realize simultaneous cycles and wait for each
- * other after the action. TWO_PHASES means that agents perceive simultaneously
- * then wait for each others and then decide and act simultaneously and finally
- * wait for each others.
- */
- public static ExecutionPolicy executionPolicy = ExecutionPolicy.ONE_PHASE;
-
- /**
- * By default, mas made with amak are meant to be executed on a graphical
- * environment. However, some may need to execute a mas without any GUI. To
- * guarantee the well functioning of this option, you have to check that you
- * only render stuff in methods such as onUpdaterRender
- * onRenderingInitialization... Also, do not forget to set your schedulers to
- * HIDDEN or DEFAULT
- */
- public static boolean commandLineMode = false;
-
- /**
- * By default AMAK will wait for all graphical update to finish before
- * moving on to the next cycle. This will likely slow down your amas, but
- * you'll be able to see it in real time.
- * If you set it to false, you have to make sure that the GUI can keep up,
- * or else you may experience freeze on the GUI.
- */
- public static boolean waitForGUI = true;
-}
+package fr.irit.smac.amak;
+
+import fr.irit.smac.amak.Amas.ExecutionPolicy;
+
+/**
+ * This class is used to define global configuration BEFORE calling any other
+ * classes/methods of the framework.
+ *
+ * @author Alexandre Perles
+ *
+ */
+public class Configuration {
+ /**
+ * The maximal number of threads that can be executed simultaneously
+ */
+ public static int allowedSimultaneousAgentsExecution = 1;
+ /**
+ * The execution policy refers to the synchronization between agents execution.
+ * ONE_PHASE means that agents can realize simultaneous cycles and wait for each
+ * other after the action. TWO_PHASES means that agents perceive simultaneously
+ * then wait for each others and then decide and act simultaneously and finally
+ * wait for each others.
+ */
+ public static ExecutionPolicy executionPolicy = ExecutionPolicy.ONE_PHASE;
+
+ /**
+ * By default, mas made with amak are meant to be executed on a graphical
+ * environment. However, some may need to execute a mas without any GUI. To
+ * guarantee the well functioning of this option, you have to check that you
+ * only render stuff in methods such as onUpdaterRender
+ * onRenderingInitialization... Also, do not forget to set your schedulers to
+ * HIDDEN or DEFAULT
+ */
+ public static boolean commandLineMode = false;
+
+ /**
+ * By default AMAK will wait for all graphical update to finish before
+ * moving on to the next cycle. This will likely slow down your amas, but
+ * you'll be able to see it in real time.
+ * If you set it to false, you have to make sure that the GUI can keep up,
+ * or else you may experience freeze on the GUI.
+ */
+ public static boolean waitForGUI = true;
+
+
+ /**
+ * By default AMAK will wait for 1 sec before updating the plots
+ */
+ public static double plotMilliSecondsUpdate = 1000;
+}
diff --git a/AMAKFX/src/fr/irit/smac/amak/examples/asyncrandomants/AsyncAntsLaunchExample.java b/AMAKFX/src/fr/irit/smac/amak/examples/asyncrandomants/AsyncAntsLaunchExample.java
deleted file mode 100644
index 7b295f64e71a469ace234de3e827fee863546929..0000000000000000000000000000000000000000
--- a/AMAKFX/src/fr/irit/smac/amak/examples/asyncrandomants/AsyncAntsLaunchExample.java
+++ /dev/null
@@ -1,40 +0,0 @@
-package fr.irit.smac.amak.examples.asyncrandomants;
-
-import fr.irit.smac.amak.Configuration;
-import fr.irit.smac.amak.examples.randomants.AntExample;
-import fr.irit.smac.amak.examples.randomants.AntHillExample;
-import fr.irit.smac.amak.examples.randomants.WorldExample;
-import fr.irit.smac.amak.ui.MainWindow;
-import javafx.scene.control.Label;
-import javafx.scene.layout.Pane;
-
-/**
- * Class aiming at starting the mas-less ants system
- *
- * @author perles
- *
- */
-public class AsyncAntsLaunchExample {
-
- /**
- * Launch method
- *
- * @param args
- * Main arguments
- */
- public static void main(String[] args) {
- Configuration.allowedSimultaneousAgentsExecution = 4;
- WorldExample env = new WorldExample();
- AntHillExample amas = new AntHillExample(env);
- for (int i = 0; i < 50; i++)
- new AntExample(amas, 0, 0);
-
- Pane panel = new Pane();
- String content = "Async AntHill simulation\n\n" + "Ants move randomly.\n"
- + "This demo is here to show AMAK asynchronous agent capacities.";
- Label label = new Label(content);
- label.setStyle("-fx-font-weight: bold;");
- panel.getChildren().add(label);
- MainWindow.setLeftPanel(panel);
- }
-}
diff --git a/AMAKFX/src/fr/irit/smac/amak/examples/asyncrandomants/package-info.java b/AMAKFX/src/fr/irit/smac/amak/examples/asyncrandomants/package-info.java
deleted file mode 100644
index 789de13bcda89c7b064448c0c987cb26fe666abd..0000000000000000000000000000000000000000
--- a/AMAKFX/src/fr/irit/smac/amak/examples/asyncrandomants/package-info.java
+++ /dev/null
@@ -1,5 +0,0 @@
-/**
- * This package contains an example showing ants moving randomly.
- * In this example, agents are fully asynchronous.
- */
-package fr.irit.smac.amak.examples.asyncrandomants;
diff --git a/AMAKFX/src/fr/irit/smac/amak/examples/philosophers/PhilosopherExample.java b/AMAKFX/src/fr/irit/smac/amak/examples/philosophers/PhilosopherExample.java
index ba7e8801d8d71d20f17ed3938b9516c72ea78ef3..c52a91a4e1126a4c0156cc9c6c2f6f0d1da37598 100644
--- a/AMAKFX/src/fr/irit/smac/amak/examples/philosophers/PhilosopherExample.java
+++ b/AMAKFX/src/fr/irit/smac/amak/examples/philosophers/PhilosopherExample.java
@@ -96,7 +96,7 @@ public class PhilosopherExample extends Agent<PhilosophersAMASExample, TableExam
}
@Override
- protected void onInitialization() {
+ public void onInitialization() {
this.id = (int) params[0];
this.left = (ForkExample) params[1];
this.right = (ForkExample) params[2];
diff --git a/AMAKFX/src/fr/irit/smac/amak/examples/randomants/AntExample.java b/AMAKFX/src/fr/irit/smac/amak/examples/randomants/AntExample.java
index 9825ec5bf17925b531acdc765b891deb00cbe909..8186b0d4b27f736e337391f0110cb3340d7b2d2d 100644
--- a/AMAKFX/src/fr/irit/smac/amak/examples/randomants/AntExample.java
+++ b/AMAKFX/src/fr/irit/smac/amak/examples/randomants/AntExample.java
@@ -36,7 +36,7 @@ public class AntExample extends Agent<AntHillExample, WorldExample> {
super(amas, startX, startY);
}
@Override
- protected void onInitialization() {
+ public void onInitialization() {
dx = (double) params[0];
dy = (double) params[1];
}
diff --git a/AMAKFX/src/fr/irit/smac/amak/tests/AsyncTest.java b/AMAKFX/src/fr/irit/smac/amak/tests/AsyncTest.java
index d5ec4abd3b8a30753382f2d632cfb21803cedde2..7fe3c2a681425c49cded0d21b96c1f51b81bb2fe 100644
--- a/AMAKFX/src/fr/irit/smac/amak/tests/AsyncTest.java
+++ b/AMAKFX/src/fr/irit/smac/amak/tests/AsyncTest.java
@@ -54,7 +54,7 @@ public class AsyncTest {
}
@Override
- protected void onInitialization() {
+ public void onInitialization() {
setAsynchronous();
}
diff --git a/AMAKFX/src/fr/irit/smac/amak/ui/AmakPlot.java b/AMAKFX/src/fr/irit/smac/amak/ui/AmakPlot.java
index 9429731628e13fb159cdc36ce0882adf6f6506c6..60a58286244634a53702a0cea0126b6a792c29aa 100644
--- a/AMAKFX/src/fr/irit/smac/amak/ui/AmakPlot.java
+++ b/AMAKFX/src/fr/irit/smac/amak/ui/AmakPlot.java
@@ -1,12 +1,16 @@
package fr.irit.smac.amak.ui;
+import java.awt.Color;
+
import org.jfree.chart.ChartFactory;
import org.jfree.chart.JFreeChart;
import org.jfree.chart.fx.ChartViewer;
+import org.jfree.chart.plot.XYPlot;
import org.jfree.chart.renderer.xy.SamplingXYLineRenderer;
import org.jfree.data.xy.XYSeries;
import org.jfree.data.xy.XYSeriesCollection;
+import fr.irit.smac.amak.Configuration;
import fr.irit.smac.amak.tools.RunLaterHelper;
import javafx.animation.KeyFrame;
import javafx.animation.Timeline;
@@ -63,12 +67,17 @@ public class AmakPlot {
if(useSamplingRenderer) {
chart.getXYPlot().setRenderer(new SamplingXYLineRenderer());
}
+ XYPlot plot = (XYPlot)chart.getPlot();
+ plot.setDomainGridlinesVisible(true);
+ plot.setDomainGridlinePaint(Color.lightGray);
+ plot.setRangeGridlinePaint(Color.lightGray);
break;
default:
System.err.println("AmakPlot : unknow ChartType \""+chartType+"\".");
break;
}
chart.setAntiAlias(false);
+ chart.getPlot().setBackgroundPaint(Color.WHITE);
if(autoAdd) {
add(this);
}
@@ -149,7 +158,7 @@ public class AmakPlot {
if(!getNotifySent()) {
setNotifySent();
Timeline tl = new Timeline(new KeyFrame(
- Duration.millis(1000),
+ Duration.millis(Configuration.plotMilliSecondsUpdate),
ae -> {seriesCollection.setNotify(true);; resetNotifySent();}));
tl.play();
}
diff --git a/AMAKFX/src/fr/irit/smac/amak/ui/DraggableTab.java b/AMAKFX/src/fr/irit/smac/amak/ui/DraggableTab.java
index cc693fe3b5a0c93bf288ce892fb682466ce86be7..4962d02921e1f2c083a427da423132723e80fc14 100644
--- a/AMAKFX/src/fr/irit/smac/amak/ui/DraggableTab.java
+++ b/AMAKFX/src/fr/irit/smac/amak/ui/DraggableTab.java
@@ -33,11 +33,6 @@ public class DraggableTab extends Tab {
private void setupDragAction() {
- // create new data format if it does not exist
- if(DataFormat.lookupMimeType("DraggableTab") == null) {
- new DataFormat("DraggableTab");
- }
-
// move text to label graphic:
// that way we have something that we can drag
if (this.getText() != null && ! this.getText().isEmpty()) {
@@ -132,6 +127,12 @@ public class DraggableTab extends Tab {
ClipboardContent content = new ClipboardContent();
// dragboard must have some content, but we need it to be a Tab, which isn't supported (Tab is not Serializable)
// So we just put arbitrary content in the dragbaord, and store our tab in a global variable
+
+ // create new data format if it does not exist
+ if(DataFormat.lookupMimeType("DraggableTab") == null) {
+ new DataFormat("DraggableTab");
+ }
+
content.put(DataFormat.lookupMimeType("DraggableTab"), "This string is not meant to be used");
dragboard.setContent(content);
dragboard.setDragView(graphic.snapshot(null, null));
diff --git a/AMAKFX/src/fr/irit/smac/amak/ui/MainWindow.java b/AMAKFX/src/fr/irit/smac/amak/ui/MainWindow.java
index f8fe92a21b32ef5ffb617fb30a85f43a002e9ef8..a38de7c2f68079efaa63159998950fa45645e70d 100644
--- a/AMAKFX/src/fr/irit/smac/amak/ui/MainWindow.java
+++ b/AMAKFX/src/fr/irit/smac/amak/ui/MainWindow.java
@@ -149,14 +149,14 @@ public class MainWindow extends Application {
* The action to be executed when the window is closed
*/
public static void addOnCloseAction(Runnable onClose) {
- instance().closeActions.add(onClose);
+ Runtime.getRuntime().addShutdownHook(new Thread() {
+ public void run() { onClose.run(); }
+ });
}
- private List<Runnable> closeActions = new ArrayList<>();
@Override
public void stop() throws Exception {
super.stop();
- closeActions.forEach(Runnable::run);
System.exit(0);
}
diff --git a/AMAKFX/src/fr/irit/smac/amak/ui/VUI.java b/AMAKFX/src/fr/irit/smac/amak/ui/VUI.java
index d679352e4310a025b09998c3f5d94a5fb5f93698..136cb472ac33fbffb9e2f7c7ddda551fe2384d81 100644
--- a/AMAKFX/src/fr/irit/smac/amak/ui/VUI.java
+++ b/AMAKFX/src/fr/irit/smac/amak/ui/VUI.java
@@ -197,7 +197,7 @@ public class VUI {
toolbar.getItems().add(resetButton);
canvas = new Pane();
- canvas.setBackground(new Background(new BackgroundFill(Color.GAINSBORO, CornerRadii.EMPTY, Insets.EMPTY)));
+ canvas.setBackground(new Background(new BackgroundFill(Color.WHITE, CornerRadii.EMPTY, Insets.EMPTY)));
// clip the canvas (avoid drawing outside of it)
Rectangle clip = new Rectangle(0, 0, 0, 0);
clip.widthProperty().bind(canvas.widthProperty());
@@ -331,7 +331,7 @@ public class VUI {
* @return the Y on screen distance
*/
public double worldToScreenY(double y) {
- return (y + getWorldOffsetY()) * getZoomFactor();
+ return (-y + getWorldOffsetY()) * getZoomFactor();
}
/**
@@ -355,7 +355,7 @@ public class VUI {
* @return the Y in the world distance
*/
public double screenToWorldY(double y) {
- return y / getZoomFactor() - getWorldOffsetY();
+ return -y / getZoomFactor() + getWorldOffsetY();
}
/**
diff --git a/AMAKFX/src/fr/irit/smac/amak/ui/drawables/DrawableDefaultMini.java b/AMAKFX/src/fr/irit/smac/amak/ui/drawables/DrawableDefaultMini.java
index a29171cbe8828922142568298c227068c497fd02..fc5e35d68a8c4307d0970109d4cb00b2989c970b 100644
--- a/AMAKFX/src/fr/irit/smac/amak/ui/drawables/DrawableDefaultMini.java
+++ b/AMAKFX/src/fr/irit/smac/amak/ui/drawables/DrawableDefaultMini.java
@@ -12,9 +12,9 @@ public class DrawableDefaultMini extends Drawable {
private Drawable original;
- private Rectangle rectangle;
- private StackPane stack;
- private Label label;
+ protected Rectangle rectangle;
+ protected StackPane stack;
+ protected Label label;
public DrawableDefaultMini(Drawable original) {
super(0, 0, 0, 0);
@@ -30,6 +30,11 @@ public class DrawableDefaultMini extends Drawable {
original.addLinkedDrawable("mini", this);
this.addLinkedDrawable("original", original);
+ defaultInit();
+ }
+
+ @Override
+ protected void defaultInit() {
getNode().addEventHandler(MouseEvent.ANY, new EventHandler<MouseEvent>() {
@Override
public void handle(MouseEvent event) {
diff --git a/AMAKFX/src/fr/irit/smac/amak/ui/drawables/DrawablePoint.java b/AMAKFX/src/fr/irit/smac/amak/ui/drawables/DrawablePoint.java
index f581e965ff1c6630931f222b7f5aaa0858af8eb9..f17758a89e8b780e74d300884c1e325ea36f70ae 100644
--- a/AMAKFX/src/fr/irit/smac/amak/ui/drawables/DrawablePoint.java
+++ b/AMAKFX/src/fr/irit/smac/amak/ui/drawables/DrawablePoint.java
@@ -1,11 +1,9 @@
package fr.irit.smac.amak.ui.drawables;
-import org.kordamp.ikonli.dashicons.Dashicons;
-import org.kordamp.ikonli.javafx.FontIcon;
-
import javafx.event.EventHandler;
import javafx.scene.Node;
import javafx.scene.input.MouseEvent;
+import javafx.scene.shape.SVGPath;
/**
* Drawable to point things on the VUI, use a '+' icon as graphical representation.
@@ -14,11 +12,11 @@ import javafx.scene.input.MouseEvent;
*/
public class DrawablePoint extends Drawable {
- private FontIcon icon;
+ private SVGPath svg = new SVGPath();
public DrawablePoint(double dx, double dy) {
- super(dx, dy, 10, 10);
- icon = FontIcon.of(Dashicons.PLUS_LIGHT);
+ super(dx, dy, 0.5, 0.5);
+ svg.setContent("M24 10h-10v-10h-4v10h-10v4h10v10h4v-10h10z");
getNode().addEventHandler(MouseEvent.ANY, new EventHandler<MouseEvent>() {
@Override
public void handle(MouseEvent event) {
@@ -26,47 +24,42 @@ public class DrawablePoint extends Drawable {
}
});
}
-
- @Override
- public Drawable move(double dx, double dy) {
- return super.move(dx, dy+getHeight());
- }
@Override
public void _onDraw() {
- icon.setFill(color);
- icon.setIconSize((int)Math.ceil(getRenderedWidth()));
- icon.setX(left());
- icon.setY(top());
+ svg.setFill(color);
+ svg.setScaleX(getRenderedWidth());
+ svg.setScaleY(getRenderedHeight());
+ // the render has an offset, 10 look like a good value
+ svg.setTranslateX(left()-10);
+ svg.setTranslateY(top()-10);
}
@Override
protected void _hide() {
- icon.setVisible(false);
+ svg.setVisible(false);
}
@Override
public void _show() {
- icon.setVisible(true);
+ svg.setVisible(true);
}
@Override
public Node getNode() {
- return icon;
+ return svg;
}
@Override
protected void onMouseExited(MouseEvent event) {
- icon.setIconSize((int)Math.ceil(getRenderedWidth()));
- icon.setX(left());
- icon.setY(top());
+ svg.setScaleX(getRenderedWidth());
+ svg.setScaleY(getRenderedHeight());
}
@Override
protected void onMouseEntered(MouseEvent event) {
- icon.setIconSize((int)Math.ceil(getRenderedWidth()*1.5));
- icon.setX(left() - getRenderedWidth()*0.25 );
- icon.setY(top() + getRenderedWidth()*0.25);
+ svg.setScaleX(getRenderedWidth()*1.5);
+ svg.setScaleY(getRenderedHeight()*1.5);
}
}
diff --git a/AMAKFX/src/fr/irit/smac/amak/ui/drawables/DrawableRectangle.java b/AMAKFX/src/fr/irit/smac/amak/ui/drawables/DrawableRectangle.java
index 0872f653d19b06ab308e9991ca18a19c07c14180..18731b5bdd938fabe0646e42a082fed264acb569 100644
--- a/AMAKFX/src/fr/irit/smac/amak/ui/drawables/DrawableRectangle.java
+++ b/AMAKFX/src/fr/irit/smac/amak/ui/drawables/DrawableRectangle.java
@@ -22,7 +22,7 @@ public class DrawableRectangle extends Drawable {
@Override
public void _onDraw() {
rectangle.setX(left());
- rectangle.setY(top());
+ rectangle.setY(bottom());
rectangle.setWidth(getRenderedWidth());
rectangle.setHeight(getRenderedHeight());
if (strokeMode)
diff --git a/AMAKFX/tests/agent/TestAgentBasicsOperations.java b/AMAKFX/tests/agent/TestAgentBasicsOperations.java
index bd8f656981a833d66c148913d8693cd0934a5a31..4db6a03738616b9de556cc8e6871a1a7a3b6b830 100644
--- a/AMAKFX/tests/agent/TestAgentBasicsOperations.java
+++ b/AMAKFX/tests/agent/TestAgentBasicsOperations.java
@@ -1,10 +1,10 @@
package agent;
-import static org.junit.Assert.assertNotNull;
+import static org.junit.jupiter.api.Assertions.assertNotNull;
import static org.junit.jupiter.api.Assertions.assertTrue;
-import org.junit.Before;
-import org.junit.Test;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
import fr.irit.smac.amak.Agent;
import fr.irit.smac.amak.CommunicatingAgent;
@@ -16,7 +16,7 @@ public class TestAgentBasicsOperations extends ObjectsForAgentTesting {
private Agent<TestAMAS, TestEnv> agent;
- @Before
+ @BeforeEach
public void setUp() {
super.setup();
diff --git a/AMAKFX/tests/agent/TestAgentMessagingFeature.java b/AMAKFX/tests/agent/TestAgentMessagingFeature.java
index 1bcbfb95ba324321aab812ba798d45545116c2e3..8e06619335c48004ebbc18603be3c214fdc02ad5 100644
--- a/AMAKFX/tests/agent/TestAgentMessagingFeature.java
+++ b/AMAKFX/tests/agent/TestAgentMessagingFeature.java
@@ -5,10 +5,10 @@ import static org.junit.jupiter.api.Assertions.assertTrue;
import java.util.Collection;
-import org.junit.After;
-import org.junit.Before;
-import org.junit.Ignore;
-import org.junit.Test;
+import org.junit.jupiter.api.AfterEach;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Disabled;
+import org.junit.jupiter.api.Test;
import fr.irit.smac.amak.messaging.IAmakEnvelope;
import testutils.ObjectsForAgentTesting;
@@ -19,7 +19,7 @@ public class TestAgentMessagingFeature extends ObjectsForAgentTesting {
public ObjectsForMessagingTesting omt;
- @Before
+ @BeforeEach
public void omt() {
omt = new ObjectsForMessagingTesting();
}
@@ -45,7 +45,7 @@ public class TestAgentMessagingFeature extends ObjectsForAgentTesting {
* Since I was never able to make it fail reliably, I suspect a badly designed test,
* And decided to deactivate it.
*/
- @Ignore @Test
+ @Disabled @Test
public void getAllReceivedMessagesSendWithRawID() throws InterruptedException {
communicantAgent1.run();
boolean sendingSuccessful = communicantAgent1.sendMessage(omt.MSG_1, ObjectsForAgentTesting.RAW_ID3);
@@ -89,7 +89,7 @@ public class TestAgentMessagingFeature extends ObjectsForAgentTesting {
assertEquals(omt.MSG_1, msg);
}
- @After
+ @AfterEach
public void teardown() {
omt.teardown();
}
diff --git a/AMAKFX/tests/agent/TestAgentMessagingReaderAllMsg.java b/AMAKFX/tests/agent/TestAgentMessagingReaderAllMsg.java
index 5d32ebc79d6eb5a7fd5c7110850604ada16f195b..97d44f045d5f76bf17addf0c0c2cfe4c3d38e8f5 100644
--- a/AMAKFX/tests/agent/TestAgentMessagingReaderAllMsg.java
+++ b/AMAKFX/tests/agent/TestAgentMessagingReaderAllMsg.java
@@ -7,8 +7,8 @@ import java.util.Collection;
import java.util.HashSet;
import java.util.Set;
-import org.junit.After;
-import org.junit.Test;
+import org.junit.jupiter.api.AfterEach;
+import org.junit.jupiter.api.Test;
import fr.irit.smac.amak.messaging.IAmakEnvelope;
import fr.irit.smac.amak.messaging.IAmakMessage;
@@ -53,7 +53,7 @@ public class TestAgentMessagingReaderAllMsg extends ObjectsForAgentTesting {
}
- @After
+ @AfterEach
public void teardown() {
omt.teardown();
}
diff --git a/AMAKFX/tests/agent/TestAgentTwoPhaseScheduling.java b/AMAKFX/tests/agent/TestAgentTwoPhaseScheduling.java
index 6dbbb3a2666ab84cf4f216753425058ef9a4a066..5457b79b99c9e4b818496bb87413d1ba1273ac93 100644
--- a/AMAKFX/tests/agent/TestAgentTwoPhaseScheduling.java
+++ b/AMAKFX/tests/agent/TestAgentTwoPhaseScheduling.java
@@ -1,14 +1,15 @@
package agent;
-import static org.junit.Assert.assertFalse;
+
import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertFalse;
import java.util.concurrent.Semaphore;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicInteger;
-import org.junit.Before;
-import org.junit.Test;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
import fr.irit.smac.amak.Amas;
import fr.irit.smac.amak.CommunicatingAgent;
@@ -25,8 +26,9 @@ public class TestAgentTwoPhaseScheduling {
private TestAMAS amas;
private static final Semaphore semaphoreToCreateBlockingState = new Semaphore(1);
- @Before
+ @BeforeEach
public void setup() {
+ Configuration.commandLineMode = true;
ObjectsForAgentTesting o = new ObjectsForAgentTesting();
TestEnv env = o.new TestEnv();
amas = new TestAMAS(env);
@@ -53,7 +55,7 @@ public class TestAgentTwoPhaseScheduling {
System.out.println("main : wait for token");
boolean hasToken = semaphoreToWaitAgentEnding.tryAcquire(2, 10, TimeUnit.SECONDS);
System.out.println("main : token release or expire, hasToken=" + hasToken);
- assertFalse("None token should be available !", hasToken);
+ assertFalse(hasToken, "None token should be available !");
assertEquals(1, perceptionIsDone.get());
assertEquals(0, decideAndActDoneWithoutAllPerceptions.get());
}
diff --git a/AMAKFX/tests/messaging/TestCustomMetaData.java b/AMAKFX/tests/messaging/TestCustomMetaData.java
index 4acddb6ecf61546d40969235e1172a4195b0f3ce..1801871a5cd18b6172da6647a7f0c522a84c0ec7 100644
--- a/AMAKFX/tests/messaging/TestCustomMetaData.java
+++ b/AMAKFX/tests/messaging/TestCustomMetaData.java
@@ -1,12 +1,12 @@
package messaging;
-import static org.junit.Assert.assertTrue;
-import static org.junit.Assert.fail;
import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertTrue;
+import static org.junit.jupiter.api.Assertions.fail;
import java.util.List;
-import org.junit.Test;
+import org.junit.jupiter.api.Test;
import fr.irit.smac.amak.messaging.IAmakEnvelope;
import fr.irit.smac.amak.messaging.IAmakMessage;
diff --git a/AMAKFX/tests/messaging/TestsBasicsOperations.java b/AMAKFX/tests/messaging/TestsBasicsOperations.java
index c6b12a8be0ca90e4bc4f4da951b4908beb29acea..9656bd1e8d1c7818ef6810d604ec231f009f32eb 100644
--- a/AMAKFX/tests/messaging/TestsBasicsOperations.java
+++ b/AMAKFX/tests/messaging/TestsBasicsOperations.java
@@ -1,12 +1,13 @@
package messaging;
-import static org.junit.Assert.assertTrue;
-import static org.junit.Assert.fail;
+
import static org.junit.jupiter.api.Assertions.assertEquals;
+import static org.junit.jupiter.api.Assertions.assertTrue;
+import static org.junit.jupiter.api.Assertions.fail;
import java.util.List;
-import org.junit.Test;
+import org.junit.jupiter.api.Test;
import fr.irit.smac.amak.messaging.IAmakEnvelope;
import fr.irit.smac.amak.messaging.IAmakMessage;
diff --git a/AMAKFX/tests/testutils/ObjectsForAgentTesting.java b/AMAKFX/tests/testutils/ObjectsForAgentTesting.java
index af137a80f53120a0b3439b5228a739b702cfd0c2..a029283fb9d31eb6291af84c3594ce5acab782c9 100644
--- a/AMAKFX/tests/testutils/ObjectsForAgentTesting.java
+++ b/AMAKFX/tests/testutils/ObjectsForAgentTesting.java
@@ -1,6 +1,7 @@
package testutils;
-import org.junit.Before;
+
+import org.junit.jupiter.api.BeforeEach;
import fr.irit.smac.amak.Amas;
import fr.irit.smac.amak.CommunicatingAgent;
@@ -18,7 +19,7 @@ public class ObjectsForAgentTesting {
public TestEnv env;
- @Before
+ @BeforeEach
public void setup() {
Configuration.commandLineMode = true;
diff --git a/AMAKFX/tests/testutils/ObjectsForMessagingTesting.java b/AMAKFX/tests/testutils/ObjectsForMessagingTesting.java
index 3f9bde46ec343c5edf6afca337ec72e7d5512a17..b3f759497d7ae713ee3c15bcb12f1feef353f3e3 100644
--- a/AMAKFX/tests/testutils/ObjectsForMessagingTesting.java
+++ b/AMAKFX/tests/testutils/ObjectsForMessagingTesting.java
@@ -1,6 +1,8 @@
package testutils;
-import org.junit.After;
+
+
+import org.junit.jupiter.api.AfterEach;
import fr.irit.smac.amak.aid.AddressableAID;
import fr.irit.smac.amak.internal.messaging.ImplMessagingServiceAgentMessaging;
@@ -52,7 +54,7 @@ public class ObjectsForMessagingTesting {
return address;
}
- @After
+ @AfterEach
public void teardown() {
messagingServices.disposeAll();
}
diff --git a/AMOEBAonAMAK/README.md b/AMOEBAonAMAK/README.md
deleted file mode 100644
index daac3b82884bc2879d8684289a57e32b486695ba..0000000000000000000000000000000000000000
--- a/AMOEBAonAMAK/README.md
+++ /dev/null
@@ -1,17 +0,0 @@
-# AMOEBA on AMAK
-An AMOEBA3 port on AMAK.
-
-## Quick start
-```Java
-// Create a world and a studied system for your amoeba
-World world = new World();
-StudiedSystem studiedSystem = new F_XY_System(50.0);
-AMOEBA amoeba = new AMOEBA(world, studiedSystem);
-// Create a backup system for the amoeba
-IBackupSystem backupSystem = new BackupSystem(amoeba);
-// Load a configuration matching the studied system
-File file = new File("resources\\twoDimensionsLauncher.xml");
-backupSystem.loadXML(file);
-// The amoeba is ready to be used
-```
-You can find a more complete exemple at `experiment.Main.java`.
\ No newline at end of file
diff --git a/AMOEBAonAMAK/pom.xml b/AMOEBAonAMAK/pom.xml
index 1139b738a5679480bef70904d69ee65dd22d6963..b89b9ee21529946ec79bec166981a04df858397a 100644
--- a/AMOEBAonAMAK/pom.xml
+++ b/AMOEBAonAMAK/pom.xml
@@ -18,14 +18,7 @@
<build>
<sourceDirectory>src</sourceDirectory>
- <resources>
- <resource>
- <directory>src</directory>
- <excludes>
- <exclude>**/*.java</exclude>
- </excludes>
- </resource>
- </resources>
+ <testSourceDirectory>tests</testSourceDirectory>
</build>
<dependencies>
@@ -35,7 +28,12 @@
<version>11</version>
</dependency>
- <!-- AMAK -->
+ <dependency>
+ <groupId>edu.brown.cs.burlap</groupId>
+ <artifactId>java_rosbridge</artifactId>
+ <version>2.0.1</version>
+ </dependency>
+
<dependency>
<groupId>AMOEBA</groupId>
<artifactId>AMAKFX</artifactId>
@@ -53,6 +51,14 @@
<artifactId>commons-math3</artifactId>
<version>3.5</version>
</dependency>
+
+ <!-- Python integration -->
+ <dependency>
+ <groupId>net.sf.py4j</groupId>
+ <artifactId>py4j</artifactId>
+ <version>0.10.8.1</version>
+ </dependency>
+
</dependencies>
</project>
\ No newline at end of file
diff --git a/AMOEBAonAMAK/resources/100DimensionsLauncher.xml b/AMOEBAonAMAK/resources/100DimensionsLauncher.xml
index cfd42e6dbd345acb0d93cca857fbd7d90b3d0a76..8b72c0c402aefd916b62e890b7d3b994b317258a 100644
--- a/AMOEBAonAMAK/resources/100DimensionsLauncher.xml
+++ b/AMOEBAonAMAK/resources/100DimensionsLauncher.xml
@@ -8,110 +8,110 @@
<StartingAgents>
- <Sensor Name="px1" ></Sensor>
- <Sensor Name="px2" ></Sensor>
- <Sensor Name="px3" ></Sensor>
- <Sensor Name="px4" ></Sensor>
- <Sensor Name="px5" ></Sensor>
- <Sensor Name="px6" ></Sensor>
- <Sensor Name="px7" ></Sensor>
- <Sensor Name="px8" ></Sensor>
- <Sensor Name="px9" ></Sensor>
- <Sensor Name="px10" ></Sensor>
- <Sensor Name="px11" ></Sensor>
- <Sensor Name="px12" ></Sensor>
- <Sensor Name="px13" ></Sensor>
- <Sensor Name="px14" ></Sensor>
- <Sensor Name="px15" ></Sensor>
- <Sensor Name="px16" ></Sensor>
- <Sensor Name="px17" ></Sensor>
- <Sensor Name="px18" ></Sensor>
- <Sensor Name="px19" ></Sensor>
- <Sensor Name="px20" ></Sensor>
- <Sensor Name="px21" ></Sensor>
- <Sensor Name="px22" ></Sensor>
- <Sensor Name="px23" ></Sensor>
- <Sensor Name="px24" ></Sensor>
- <Sensor Name="px25" ></Sensor>
- <Sensor Name="px26" ></Sensor>
- <Sensor Name="px27" ></Sensor>
- <Sensor Name="px28" ></Sensor>
- <Sensor Name="px29" ></Sensor>
- <Sensor Name="px30" ></Sensor>
- <Sensor Name="px31" ></Sensor>
- <Sensor Name="px32" ></Sensor>
- <Sensor Name="px33" ></Sensor>
- <Sensor Name="px34" ></Sensor>
- <Sensor Name="px35" ></Sensor>
- <Sensor Name="px36" ></Sensor>
- <Sensor Name="px37" ></Sensor>
- <Sensor Name="px38" ></Sensor>
- <Sensor Name="px39" ></Sensor>
- <Sensor Name="px40" ></Sensor>
- <Sensor Name="px41" ></Sensor>
- <Sensor Name="px42" ></Sensor>
- <Sensor Name="px43" ></Sensor>
- <Sensor Name="px44" ></Sensor>
- <Sensor Name="px45" ></Sensor>
- <Sensor Name="px46" ></Sensor>
- <Sensor Name="px47" ></Sensor>
- <Sensor Name="px48" ></Sensor>
- <Sensor Name="px49" ></Sensor>
- <Sensor Name="px50" ></Sensor>
- <Sensor Name="px51" ></Sensor>
- <Sensor Name="px52" ></Sensor>
- <Sensor Name="px53" ></Sensor>
- <Sensor Name="px54" ></Sensor>
- <Sensor Name="px55" ></Sensor>
- <Sensor Name="px56" ></Sensor>
- <Sensor Name="px57" ></Sensor>
- <Sensor Name="px58" ></Sensor>
- <Sensor Name="px59" ></Sensor>
- <Sensor Name="px60" ></Sensor>
- <Sensor Name="px61" ></Sensor>
- <Sensor Name="px62" ></Sensor>
- <Sensor Name="px63" ></Sensor>
- <Sensor Name="px64" ></Sensor>
- <Sensor Name="px65" ></Sensor>
- <Sensor Name="px66" ></Sensor>
- <Sensor Name="px67" ></Sensor>
- <Sensor Name="px68" ></Sensor>
- <Sensor Name="px69" ></Sensor>
- <Sensor Name="px70" ></Sensor>
- <Sensor Name="px71" ></Sensor>
- <Sensor Name="px72" ></Sensor>
- <Sensor Name="px73" ></Sensor>
- <Sensor Name="px74" ></Sensor>
- <Sensor Name="px75" ></Sensor>
- <Sensor Name="px76" ></Sensor>
- <Sensor Name="px77" ></Sensor>
- <Sensor Name="px78" ></Sensor>
- <Sensor Name="px79" ></Sensor>
- <Sensor Name="px80" ></Sensor>
- <Sensor Name="px81" ></Sensor>
- <Sensor Name="px82" ></Sensor>
- <Sensor Name="px83" ></Sensor>
- <Sensor Name="px84" ></Sensor>
- <Sensor Name="px85" ></Sensor>
- <Sensor Name="px86" ></Sensor>
- <Sensor Name="px87" ></Sensor>
- <Sensor Name="px88" ></Sensor>
- <Sensor Name="px89" ></Sensor>
- <Sensor Name="px90" ></Sensor>
- <Sensor Name="px91" ></Sensor>
- <Sensor Name="px92" ></Sensor>
- <Sensor Name="px93" ></Sensor>
- <Sensor Name="px94" ></Sensor>
- <Sensor Name="px95" ></Sensor>
- <Sensor Name="px96" ></Sensor>
- <Sensor Name="px97" ></Sensor>
- <Sensor Name="px98" ></Sensor>
- <Sensor Name="px99" ></Sensor>
- <Sensor Name="px100" ></Sensor>
+ <Sensor Name="px1" Enum="false"></Sensor>
+ <Sensor Name="px2" Enum="false"></Sensor>
+ <Sensor Name="px3" Enum="false"></Sensor>
+ <Sensor Name="px4" Enum="false"></Sensor>
+ <Sensor Name="px5" Enum="false"></Sensor>
+ <Sensor Name="px6" Enum="false"></Sensor>
+ <Sensor Name="px7" Enum="false"></Sensor>
+ <Sensor Name="px8" Enum="false"></Sensor>
+ <Sensor Name="px9" Enum="false"></Sensor>
+ <Sensor Name="px10" Enum="false"></Sensor>
+ <Sensor Name="px11" Enum="false"></Sensor>
+ <Sensor Name="px12" Enum="false"></Sensor>
+ <Sensor Name="px13" Enum="false"></Sensor>
+ <Sensor Name="px14" Enum="false"></Sensor>
+ <Sensor Name="px15" Enum="false"></Sensor>
+ <Sensor Name="px16" Enum="false"></Sensor>
+ <Sensor Name="px17" Enum="false"></Sensor>
+ <Sensor Name="px18" Enum="false"></Sensor>
+ <Sensor Name="px19" Enum="false"></Sensor>
+ <Sensor Name="px20" Enum="false"></Sensor>
+ <Sensor Name="px21" Enum="false"></Sensor>
+ <Sensor Name="px22" Enum="false"></Sensor>
+ <Sensor Name="px23" Enum="false"></Sensor>
+ <Sensor Name="px24" Enum="false"></Sensor>
+ <Sensor Name="px25" Enum="false"></Sensor>
+ <Sensor Name="px26" Enum="false"></Sensor>
+ <Sensor Name="px27" Enum="false"></Sensor>
+ <Sensor Name="px28" Enum="false"></Sensor>
+ <Sensor Name="px29" Enum="false"></Sensor>
+ <Sensor Name="px30" Enum="false"></Sensor>
+ <Sensor Name="px31" Enum="false"></Sensor>
+ <Sensor Name="px32" Enum="false"></Sensor>
+ <Sensor Name="px33" Enum="false"></Sensor>
+ <Sensor Name="px34" Enum="false"></Sensor>
+ <Sensor Name="px35" Enum="false"></Sensor>
+ <Sensor Name="px36" Enum="false"></Sensor>
+ <Sensor Name="px37" Enum="false"></Sensor>
+ <Sensor Name="px38" Enum="false"></Sensor>
+ <Sensor Name="px39" Enum="false"></Sensor>
+ <Sensor Name="px40" Enum="false"></Sensor>
+ <Sensor Name="px41" Enum="false"></Sensor>
+ <Sensor Name="px42" Enum="false"></Sensor>
+ <Sensor Name="px43" Enum="false"></Sensor>
+ <Sensor Name="px44" Enum="false"></Sensor>
+ <Sensor Name="px45" Enum="false"></Sensor>
+ <Sensor Name="px46" Enum="false"></Sensor>
+ <Sensor Name="px47" Enum="false"></Sensor>
+ <Sensor Name="px48" Enum="false"></Sensor>
+ <Sensor Name="px49" Enum="false"></Sensor>
+ <Sensor Name="px50" Enum="false"></Sensor>
+ <Sensor Name="px51" Enum="false"></Sensor>
+ <Sensor Name="px52" Enum="false"></Sensor>
+ <Sensor Name="px53" Enum="false"></Sensor>
+ <Sensor Name="px54" Enum="false"></Sensor>
+ <Sensor Name="px55" Enum="false"></Sensor>
+ <Sensor Name="px56" Enum="false"></Sensor>
+ <Sensor Name="px57" Enum="false"></Sensor>
+ <Sensor Name="px58" Enum="false"></Sensor>
+ <Sensor Name="px59" Enum="false"></Sensor>
+ <Sensor Name="px60" Enum="false"></Sensor>
+ <Sensor Name="px61" Enum="false"></Sensor>
+ <Sensor Name="px62" Enum="false"></Sensor>
+ <Sensor Name="px63" Enum="false"></Sensor>
+ <Sensor Name="px64" Enum="false"></Sensor>
+ <Sensor Name="px65" Enum="false"></Sensor>
+ <Sensor Name="px66" Enum="false"></Sensor>
+ <Sensor Name="px67" Enum="false"></Sensor>
+ <Sensor Name="px68" Enum="false"></Sensor>
+ <Sensor Name="px69" Enum="false"></Sensor>
+ <Sensor Name="px70" Enum="false"></Sensor>
+ <Sensor Name="px71" Enum="false"></Sensor>
+ <Sensor Name="px72" Enum="false"></Sensor>
+ <Sensor Name="px73" Enum="false"></Sensor>
+ <Sensor Name="px74" Enum="false"></Sensor>
+ <Sensor Name="px75" Enum="false"></Sensor>
+ <Sensor Name="px76" Enum="false"></Sensor>
+ <Sensor Name="px77" Enum="false"></Sensor>
+ <Sensor Name="px78" Enum="false"></Sensor>
+ <Sensor Name="px79" Enum="false"></Sensor>
+ <Sensor Name="px80" Enum="false"></Sensor>
+ <Sensor Name="px81" Enum="false"></Sensor>
+ <Sensor Name="px82" Enum="false"></Sensor>
+ <Sensor Name="px83" Enum="false"></Sensor>
+ <Sensor Name="px84" Enum="false"></Sensor>
+ <Sensor Name="px85" Enum="false"></Sensor>
+ <Sensor Name="px86" Enum="false"></Sensor>
+ <Sensor Name="px87" Enum="false"></Sensor>
+ <Sensor Name="px88" Enum="false"></Sensor>
+ <Sensor Name="px89" Enum="false"></Sensor>
+ <Sensor Name="px90" Enum="false"></Sensor>
+ <Sensor Name="px91" Enum="false"></Sensor>
+ <Sensor Name="px92" Enum="false"></Sensor>
+ <Sensor Name="px93" Enum="false"></Sensor>
+ <Sensor Name="px94" Enum="false"></Sensor>
+ <Sensor Name="px95" Enum="false"></Sensor>
+ <Sensor Name="px96" Enum="false"></Sensor>
+ <Sensor Name="px97" Enum="false"></Sensor>
+ <Sensor Name="px98" Enum="false"></Sensor>
+ <Sensor Name="px99" Enum="false"></Sensor>
+ <Sensor Name="px100" Enum="false"></Sensor>
<Controller Name="Controller" Oracle="test">
<ErrorMargin ErrorAllowed="2000.0" AugmentationFactorError="5.0" DiminutionFactorError="0.4" MinErrorAllowed="0.1" NConflictBeforeAugmentation="40" NSuccessBeforeDiminution="80" />
- <InexactMargin InexactAllowed="500.0" AugmentationInexactError="2.5" DiminutionInexactError="0.2" MinInexactAllowed="0.05" NConflictBeforeInexactAugmentation="40" NSuccessBeforeInexactDiminution="80" />
+
</Controller>
diff --git a/AMOEBAonAMAK/resources/100DimensionsLauncherTrained1000.xml b/AMOEBAonAMAK/resources/100DimensionsLauncherTrained1000.xml
index 2b93b3581a1dd1c25121761e5f1eb8ef475f8216..b66e7628bb7ebb42f06eb2cdc9d8ca4565e98727 100644
--- a/AMOEBAonAMAK/resources/100DimensionsLauncherTrained1000.xml
+++ b/AMOEBAonAMAK/resources/100DimensionsLauncherTrained1000.xml
@@ -6,7 +6,7 @@
<StartingAgents>
<Controller Name="Controller">
<ErrorMargin ErrorAllowed="134217.72800000003" AugmentationFactorError="5.0" DiminutionFactorError="0.4" MinErrorAllowed="0.1" NConflictBeforeAugmentation="40" NSuccessBeforeDiminution="40" />
- <InexactMargin InexactAllowed="232830.64365386963" AugmentationInexactError="2.5" DiminutionInexactError="0.2" MinInexactAllowed="0.05" NConflictBeforeInexactAugmentation="40" NSuccessBeforeInexactDiminution="80" />
+
</Controller>
<Sensor Name="px1" Enum="false" />
<Sensor Name="px2" Enum="false" />
diff --git a/AMOEBAonAMAK/resources/Amoebatest.xml b/AMOEBAonAMAK/resources/Amoebatest.xml
new file mode 100644
index 0000000000000000000000000000000000000000..92fb057cba1c34c74e16a7f3777371c60deb66d3
--- /dev/null
+++ b/AMOEBAonAMAK/resources/Amoebatest.xml
@@ -0,0 +1,18 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<System>
+
+ <Configuration>
+ <Learning allowed = "true" creationOfNewContext = "true" loadPresetContext = "false"></Learning>
+ </Configuration>
+
+ <StartingAgents>
+ <Sensor Name="px" Enum="false" />
+ <Sensor Name="py" Enum="false" />
+
+ <Controller Name="Controller">
+ <ErrorMargin ErrorAllowed="2000.0" AugmentationFactorError="5.0" DiminutionFactorError="0.4" MinErrorAllowed="0.1" NConflictBeforeAugmentation="40" NSuccessBeforeDiminution="80" />
+
+ </Controller>
+ </StartingAgents>
+
+</System>
diff --git a/AMOEBAonAMAK/resources/fourDimensionsLauncher.xml b/AMOEBAonAMAK/resources/fourDimensionsLauncher.xml
index d3190af0d05d2b493a1c90ee99da5a452dc207d2..9e05fedca3f9757033faf798e57febbde599b9a0 100644
--- a/AMOEBAonAMAK/resources/fourDimensionsLauncher.xml
+++ b/AMOEBAonAMAK/resources/fourDimensionsLauncher.xml
@@ -16,7 +16,7 @@
<Controller Name="Controller">
<ErrorMargin ErrorAllowed="2000.0" AugmentationFactorError="5.0" DiminutionFactorError="0.4" MinErrorAllowed="0.1" NConflictBeforeAugmentation="40" NSuccessBeforeDiminution="80" />
- <InexactMargin InexactAllowed="500.0" AugmentationInexactError="2.5" DiminutionInexactError="0.2" MinInexactAllowed="0.05" NConflictBeforeInexactAugmentation="40" NSuccessBeforeInexactDiminution="80" />
+
</Controller>
diff --git a/AMOEBAonAMAK/resources/mnist.xml b/AMOEBAonAMAK/resources/mnist.xml
index 7dd3bf3d97b41e655371be8990b2d152c5f09d3a..d0f11f03968ef2134cf9175af537eaa8c83a0ffb 100644
--- a/AMOEBAonAMAK/resources/mnist.xml
+++ b/AMOEBAonAMAK/resources/mnist.xml
@@ -797,7 +797,7 @@
<Controller Name="Controller" Oracle="test">
<ErrorMargin ErrorAllowed="2000.0" AugmentationFactorError="5.0" DiminutionFactorError="0.4" MinErrorAllowed="0.1" NConflictBeforeAugmentation="40" NSuccessBeforeDiminution="80" />
- <InexactMargin InexactAllowed="500.0" AugmentationInexactError="2.5" DiminutionInexactError="0.2" MinInexactAllowed="0.05" NConflictBeforeInexactAugmentation="40" NSuccessBeforeInexactDiminution="80" />
+
</Controller>
diff --git a/AMOEBAonAMAK/resources/threeDimensionsLauncher.xml b/AMOEBAonAMAK/resources/threeDimensionsLauncher.xml
index 21b6dcb92b9daf759b0d3cef070165fbcb474fae..aab252c4ba35642f2ad43f4eef92fe71fe13cd1b 100644
--- a/AMOEBAonAMAK/resources/threeDimensionsLauncher.xml
+++ b/AMOEBAonAMAK/resources/threeDimensionsLauncher.xml
@@ -6,7 +6,6 @@
<Learning allowed = "true" creationOfNewContext = "true" loadPresetContext = "false"></Learning>
</Configuration>
-
<StartingAgents>
<Sensor Name="px1" Enum="false" />
@@ -14,13 +13,9 @@
<Sensor Name="px3" Enum="false" />
<Controller Name="Controller">
- <ErrorMargin ErrorAllowed="2000.0" AugmentationFactorError="5.0" DiminutionFactorError="0.4" MinErrorAllowed="0.1" NConflictBeforeAugmentation="40" NSuccessBeforeDiminution="80" />
- <InexactMargin InexactAllowed="500.0" AugmentationInexactError="2.5" DiminutionInexactError="0.2" MinInexactAllowed="0.05" NConflictBeforeInexactAugmentation="40" NSuccessBeforeInexactDiminution="80" />
+ <ErrorMargin ErrorAllowed="1.0" AugmentationFactorError="0.5" DiminutionFactorError="0.5" MinErrorAllowed="0.01" NConflictBeforeAugmentation="50" NSuccessBeforeDiminution="50" />
+
</Controller>
-
-
-
</StartingAgents>
-
</System>
diff --git a/AMOEBAonAMAK/resources/threeDimensionsLauncherUnity.xml b/AMOEBAonAMAK/resources/threeDimensionsLauncherUnity.xml
new file mode 100644
index 0000000000000000000000000000000000000000..ea0012a0810f27f03e731cb139e54089cb29018e
--- /dev/null
+++ b/AMOEBAonAMAK/resources/threeDimensionsLauncherUnity.xml
@@ -0,0 +1,21 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<System>
+
+ <!-- General config options -->
+ <Configuration>
+ <Learning allowed = "true" creationOfNewContext = "true" loadPresetContext = "false"></Learning>
+ </Configuration>
+
+ <StartingAgents>
+
+ <Sensor Name="px0" Enum="false" />
+ <Sensor Name="px1" Enum="false" />
+ <Sensor Name="px2" Enum="false" />
+
+ <Controller Name="Controller">
+ <ErrorMargin ErrorAllowed="1.0" AugmentationFactorError="0.5" DiminutionFactorError="0.5" MinErrorAllowed="0.01" NConflictBeforeAugmentation="50" NSuccessBeforeDiminution="50" />
+
+ </Controller>
+ </StartingAgents>
+
+</System>
diff --git a/AMOEBAonAMAK/resources/twoDimensionsLauncher.xml b/AMOEBAonAMAK/resources/twoDimensionsLauncher.xml
index 2c14ff6c21935f121f77d687355e8b8d95e77cc1..d8ef2d83d1b1f832570dc0bd9e6eb4fa600331ff 100644
--- a/AMOEBAonAMAK/resources/twoDimensionsLauncher.xml
+++ b/AMOEBAonAMAK/resources/twoDimensionsLauncher.xml
@@ -1,19 +1,20 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<System>
-
- <!-- General config options -->
- <Configuration>
- <Learning allowed = "true" creationOfNewContext = "true" loadPresetContext = "false"></Learning>
- </Configuration>
-
- <StartingAgents>
- <Sensor Name="px" Enum="false" />
- <Sensor Name="py" Enum="false" />
-
- <Controller Name="Controller">
- <ErrorMargin ErrorAllowed="2000.0" AugmentationFactorError="5.0" DiminutionFactorError="0.4" MinErrorAllowed="0.1" NConflictBeforeAugmentation="40" NSuccessBeforeDiminution="80" />
- <InexactMargin InexactAllowed="500.0" AugmentationInexactError="2.5" DiminutionInexactError="0.2" MinInexactAllowed="0.05" NConflictBeforeInexactAugmentation="40" NSuccessBeforeInexactDiminution="80" />
- </Controller>
- </StartingAgents>
-
-</System>
+<?xml version="1.0" encoding="UTF-8"?>
+<System>
+
+ <!-- General config options -->
+ <Configuration>
+ <Learning allowed = "true" creationOfNewContext = "true" loadPresetContext = "false"></Learning>
+ </Configuration>
+
+ <StartingAgents>
+
+ <Sensor Name="px0" Enum="false" />
+ <Sensor Name="px1" Enum="false" />
+
+ <Controller Name="Controller">
+ <ErrorMargin ErrorAllowed="1.0" AugmentationFactorError="0.5" DiminutionFactorError="0.5" MinErrorAllowed="0.01" NConflictBeforeAugmentation="50" NSuccessBeforeDiminution="50" />
+
+ </Controller>
+ </StartingAgents>
+
+</System>
diff --git a/AMOEBAonAMAK/src/agents/AmoebaAgent.java b/AMOEBAonAMAK/src/agents/AmoebaAgent.java
index 2834fa10bcb505f7503a47ad731f6d63d0263571..45a2c6c1ba8e1985d2d4a11c0c2075cfeff62fb5 100644
--- a/AMOEBAonAMAK/src/agents/AmoebaAgent.java
+++ b/AMOEBAonAMAK/src/agents/AmoebaAgent.java
@@ -21,14 +21,13 @@ public abstract class AmoebaAgent extends Agent<AMOEBA, World> implements Loggab
* Instantiate a new agent attached to an amoeba
* @param the amoeba
*/
- public AmoebaAgent(AMOEBA amas) {
- super(amas);
+ public AmoebaAgent(AMOEBA amas, Object... params) {
+ super(amas, params);
this.dying = false;
}
@Override
protected void onReady() {
- // TODO Auto-generated method stub
super.onReady();
logger().debug("CYCLE "+getAmas().getCycle(), "Agent %s ready.", toString());
}
diff --git a/AMOEBAonAMAK/src/agents/context/CenterRangeComparator.java b/AMOEBAonAMAK/src/agents/context/CenterRangeComparator.java
new file mode 100644
index 0000000000000000000000000000000000000000..c1f3731a357217ba9725d1732807fd271bb096a2
--- /dev/null
+++ b/AMOEBAonAMAK/src/agents/context/CenterRangeComparator.java
@@ -0,0 +1,29 @@
+package agents.context;
+
+import java.io.Serializable;
+import java.util.Comparator;
+
+import agents.percept.Percept;
+
+public class CenterRangeComparator implements Comparator<Context>, Serializable{
+
+
+ private Percept percept;
+ private String range;
+
+
+ public CenterRangeComparator(Percept percept){
+ this.percept = percept;
+ }
+
+ @Override
+ public int compare(Context c1, Context c2) {
+
+ Double r1 = new Double(c1.getRanges().get(percept).getCenter());
+ Double r2 = new Double(c2.getRanges().get(percept).getCenter());
+
+ return r1.compareTo(r2);
+
+ }
+
+}
diff --git a/AMOEBAonAMAK/src/agents/context/Context.java b/AMOEBAonAMAK/src/agents/context/Context.java
index 28b479ee6ec121fa75420a449a4f99643437f9f9..9cf57cf509fc3d7f4aad60f2750594701635e15f 100644
--- a/AMOEBAonAMAK/src/agents/context/Context.java
+++ b/AMOEBAonAMAK/src/agents/context/Context.java
@@ -3,19 +3,25 @@ package agents.context;
import java.lang.reflect.Constructor;
import java.lang.reflect.InvocationTargetException;
import java.util.ArrayList;
+import java.util.Arrays;
import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.Set;
import agents.AmoebaAgent;
import agents.context.localModel.LocalModel;
+import agents.context.localModel.LocalModelMillerRegression;
+import agents.context.localModel.TypeLocalModel;
+import agents.head.Criticalities;
+import agents.head.DynamicPerformance;
+import agents.head.EndogenousRequest;
import agents.head.Head;
+import agents.head.REQUEST;
import agents.percept.Percept;
import gui.ContextRendererFX;
import gui.RenderStrategy;
import kernel.AMOEBA;
import ncs.NCS;
+import utils.Pair;
+import utils.TRACE_LEVEL;
/**
* The core agent of AMOEBA.
@@ -23,359 +29,1505 @@ import ncs.NCS;
*/
public class Context extends AmoebaAgent {
// STATIC ---
- public static Class<? extends RenderStrategy> defaultRenderStrategy = ContextRendererFX.class;
+ public static Class<? extends RenderStrategy> defaultRenderStrategy = ContextRendererFX.class;
// ----------
-
- private Head headAgent;
+
private HashMap<Percept, Range> ranges;
- private ArrayList<Experiment> experiments;
private LocalModel localModel;
private double confidence = 0;
-
+
/**
- * The number of time the context was activated (present in validContext).
- * Used for visualization.
+ * The number of time the context was activated (present in validContext). Used
+ * for visualization.
*/
private int activations = 0;
+ private int nSelection = 0;
+ private int tickCreation;
+
+ private double action;
+
+ private Double actionProposition = null;
+
+ //private boolean valid;
+
+ private ArrayList<EndogenousRequest> waitingRequests = new ArrayList<EndogenousRequest>();
+
+ public DynamicPerformance regressionPerformance;
+ public Criticalities criticalities ;
+ public double lastDistanceToModel = -1.0;
+ public double lastAverageRegressionPerformanceIndicator = -1.0;
+
+ public static final double augmentationFactorError = 0.5;
+ public static final double diminutionFactorError = 0.66;
+ public static final double minError = 1;
+ public static final int successesBeforeDiminution = 5;
+ public static final int errorsBeforeAugmentation = 5;
+
+ public Context(AMOEBA amoeba) {
+ super(amoeba);
+ buildContext();
+ criticalities = new Criticalities(5);
+
+ regressionPerformance = new DynamicPerformance(successesBeforeDiminution, errorsBeforeAugmentation, getAmas().getHeadAgent().getAverageRegressionPerformanceIndicator(), augmentationFactorError, diminutionFactorError, minError);
+ getAmas().getEnvironment().trace(TRACE_LEVEL.EVENT,new ArrayList<String>(Arrays.asList("CTXT CREATION", this.getName())));
+ getAmas().addSpatiallyAlteredContextForUnityUI(this);
+ }
- public Context(AMOEBA amoeba, Head head) {
+ public Context(AMOEBA amoeba, Context bestNearestContext) {
super(amoeba);
- Experiment firstPoint = new Experiment();
+ buildContext(bestNearestContext);
+ getAmas().getEnvironment()
+ .trace(TRACE_LEVEL.EVENT, new ArrayList<String>(Arrays.asList("CTXT CREATION WITH GODFATHER", this.getName())));
+ criticalities = new Criticalities(5);
+
+ regressionPerformance = new DynamicPerformance(successesBeforeDiminution, errorsBeforeAugmentation, getAmas().getHeadAgent().getAverageRegressionPerformanceIndicator(), augmentationFactorError, diminutionFactorError, minError);
+ getAmas().addSpatiallyAlteredContextForUnityUI(this);
+ }
+
+ public Context(AMOEBA amoeba, Context fatherContext, HashMap<Percept, Pair<Double, Double>> contextDimensions) {
+ super(amoeba);
+ buildContext(fatherContext, contextDimensions);
+ getAmas().getEnvironment()
+ .trace(TRACE_LEVEL.EVENT, new ArrayList<String>(Arrays.asList("CTXT CREATION WITH GODFATHER AND DIM", this.getName())));
+ }
+
+ private void buildContextCommon() {
+ this.tickCreation = getAmas().getCycle();
+ action = getAmas().getHeadAgent().getOracleValue();
+ }
+
+ /**
+ * Builds the context.
+ */
+ private void buildContext() {
+
+ buildContextCommon();
+
+ Experiment firstPoint = new Experiment(this);
+ ArrayList<Percept> var = getAmas().getPercepts();
+ for (Percept p : var) {
+ Range r;
+
+ //Pair<Double, Double> radiuses = getAmas().getHeadAgent().getMaxRadiusesForContextCreation(p);
+ Pair<Double, Double> radiuses = getAmas().getHeadAgent().getRadiusesForContextCreation(p);
+
+ r = new Range(this, p.getValue() - radiuses.getA(), p.getValue() + radiuses.getB(), 0, true, true, p);
+
+ // r = new Range(this, v.getValue() - radius, v.getValue() + radius, 0, true,
+ // true, v, world);
+ ranges.put(p, r);
+ ranges.get(p).setValue(p.getValue());
+
+ firstPoint.addDimension(p, p.getValue());
+
+ p.addContextProjection(this);
+ }
+
+ //expand();
+
+ localModel = getAmas().buildLocalModel(this);
+ firstPoint.setOracleProposition(getAmas().getHeadAgent().getOracleValue());
+ // world.trace(new ArrayList<String>(Arrays.asList(this.getName(),"NEW EXP",
+ // firstPoint.toString())));
+
+ localModel.updateModel(this.getCurrentExperiment(), getAmas().data.learningSpeed);
+ getAmas().addAlteredContext(this);
+ this.setName(String.valueOf(this.hashCode()));
+
+ // world.trace(new ArrayList<String>(Arrays.asList(this.getName(), "EXPS")));
+ }
+
+ private void buildContext(Context fatherContext, HashMap<Percept, Pair<Double, Double>> contextDimensions) {
+
+ buildContextCommon();
+
+ ArrayList<Percept> var = getAmas().getPercepts();
+ for (Percept pct : var) {
+ Range r;
+ double center = contextDimensions.get(pct).getA();
+ double length = contextDimensions.get(pct).getB();
+ r = new Range(this, center - length / 2, center + length / 2, 0, true, true, pct);
+
+ ranges.put(pct, r);
+ ranges.get(pct).setValue(center);
+
+ pct.addContextProjection(this);
+ }
+
+ // expand();
+
+ this.confidence = fatherContext.confidence;
+ if (fatherContext.getLocalModel().getType() == TypeLocalModel.MILLER_REGRESSION) {
+
+ this.localModel = new LocalModelMillerRegression(this);
+ // this.formulaLocalModel = ((LocalModelMillerRegression)
+ // bestNearestContext.localModel).getFormula(bestNearestContext);
+ Double[] coef = ((LocalModelMillerRegression) fatherContext.localModel).getCoef();
+ ((LocalModelMillerRegression) this.localModel).setCoef(coef);
+ this.actionProposition = ((LocalModelMillerRegression) fatherContext.localModel)
+ .getProposition();
+ }
+
+ getAmas().addAlteredContext(this);
+ this.setName(String.valueOf(this.hashCode()));
+
+ // world.trace(new ArrayList<String>(Arrays.asList(this.getName(), "EXPS")));
+ }
+
+ private void buildContext(Context bestNearestContext) {
+
+ buildContextCommon();
+
+ Experiment firstPoint = new Experiment(this);
+ ArrayList<Percept> var = getAmas().getPercepts();
+ for (Percept v : var) {
+ Range r;
+ //Pair<Double, Double> radiuses = getAmas().getHeadAgent().getMaxRadiusesForContextCreation(v);
+ Pair<Double, Double> radiuses = getAmas().getHeadAgent().getRadiusesForContextCreation(v);
+
+
+ r = new Range(this, v.getValue() - radiuses.getA(), v.getValue() + radiuses.getB(), 0, true, true, v);
+
+ ranges.put(v, r);
+ ranges.get(v).setValue(v.getValue());
+
+ firstPoint.addDimension(v, v.getValue());
+
+ v.addContextProjection(this);;
+ }
+
+ //expand();
+
+ this.confidence = bestNearestContext.confidence;
+ if (bestNearestContext.getLocalModel().getType() == TypeLocalModel.MILLER_REGRESSION) {
+
+ this.localModel = new LocalModelMillerRegression(this);
+ // this.formulaLocalModel = ((LocalModelMillerRegression)
+ // bestNearestContext.localModel).getFormula(bestNearestContext);
+ Double[] coef = ((LocalModelMillerRegression) bestNearestContext.localModel).getCoef();
+ ((LocalModelMillerRegression) this.localModel).setCoef(coef);
+ this.actionProposition = ((LocalModelMillerRegression) bestNearestContext.localModel)
+ .getProposition();
+ }
+
+ localModel.setFirstExperiments(new ArrayList<Experiment>(bestNearestContext.getLocalModel().getFirstExperiments()));
+
+ localModel.updateModel(this.getCurrentExperiment(), getAmas().data.learningSpeed);
+
+ getAmas().addAlteredContext(this);
+ this.setName(String.valueOf(this.hashCode()));
+
+ }
+
+ public ArrayList<Context> getContextsOnAPerceptDirectionFromContextsNeighbors(ArrayList<Context> contextNeighbors,
+ Percept pctDirection) {
+ ArrayList<Context> contexts = new ArrayList<Context>();
+
+ boolean test = true;
+ for (Context ctxtNeigbor : contextNeighbors) {
+ for (Percept pct : ranges.keySet()) {
+ if (pct != pctDirection) {
+ test = test && (this.ranges.get(pct).distance(ctxtNeigbor.getRanges().get(pct)) < 0);
+ }
+ }
+ if (test) {
+ contexts.add(ctxtNeigbor);
+ }
+ }
+ return contexts;
+ }
+
+ public ArrayList<Context> getContextsOnAPerceptDirectionFromContextsNeighbors(ArrayList<Context> contextNeighbors,
+ Percept pctDirection, SpatialContext expandingContext) {
+ ArrayList<Context> contexts = new ArrayList<Context>();
+
+ boolean test = true;
+ for (Context ctxtNeigbor : contextNeighbors) {
+ for (Percept pct : ranges.keySet()) {
+ if (pct != pctDirection) {
+
+ test = test && (expandingContext.distance(pct, ctxtNeigbor.getRanges().get(pct)) < -0.0001);
+ }
+ }
+ if (test) {
+ contexts.add(ctxtNeigbor);
+ }
+
+ test = true;
+ }
+ return contexts;
+ }
+
+ public void expand() {
+ ArrayList<Context> neighborsOnOneDirection;
+ HashMap<Percept, SpatialContext> alternativeContexts = new HashMap<Percept, SpatialContext>();
+ double maxVolume = this.getVolume();
+ double currentVolume;
+ SpatialContext maxVolumeSpatialContext = null;
+
+ for (Percept fixedPct : ranges.keySet()) {
+
+ alternativeContexts.put(fixedPct, new SpatialContext(this));
+
+ for (Percept pctDirectionForExpanding : ranges.keySet()) {
+
+ if (pctDirectionForExpanding != fixedPct) {
+
+ neighborsOnOneDirection = getContextsOnAPerceptDirectionFromContextsNeighbors(
+ getAmas().getHeadAgent().getActivatedNeighborsContexts(), pctDirectionForExpanding,
+ alternativeContexts.get(fixedPct));
+
+ Pair<Double, Double> expandingRadiuses = getMaxExpansionsForContextExpansionAfterCreation(
+ neighborsOnOneDirection, pctDirectionForExpanding);
+ alternativeContexts.get(fixedPct).expandEnd(pctDirectionForExpanding, expandingRadiuses.getB());
+ alternativeContexts.get(fixedPct).expandStart(pctDirectionForExpanding, expandingRadiuses.getA());
+ }
+ }
+
+ currentVolume = alternativeContexts.get(fixedPct).getVolume();
+ if (currentVolume > maxVolume) {
+ maxVolume = currentVolume;
+ maxVolumeSpatialContext = alternativeContexts.get(fixedPct);
+ }
+
+ }
+ if (maxVolumeSpatialContext != null) {
+ matchSpatialContextRanges(maxVolumeSpatialContext);
+ }
+ }
+
+ public void matchSpatialContextRanges(SpatialContext biggerContextForCreation) {
+ for (Percept pct : ranges.keySet()) {
+ ranges.get(pct).setStart(biggerContextForCreation.getStart(pct));
+ ranges.get(pct).setEnd(biggerContextForCreation.getEnd(pct));
+ }
+ }
+
+ public Pair<Double, Double> getMaxExpansionsForContextExpansionAfterCreation(
+ ArrayList<Context> contextNeighborsInOneDirection, Percept pct) {
+
+
+ double startRadiusFromCreation = Math.abs(pct.getValue() - this.getRanges().get(pct).getStart());
+ double endRadiusFromCreation = Math.abs(pct.getValue() - this.getRanges().get(pct).getEnd());
+// Pair<Double, Double> maxExpansions = new Pair<Double, Double>(
+// Math.min(pct.getRadiusContextForCreation() - startRadiusFromCreation,
+// Math.abs(pct.getMin() - ranges.get(pct).getStart())),
+// Math.min(pct.getRadiusContextForCreation() - endRadiusFromCreation,
+// Math.abs(pct.getMax() - ranges.get(pct).getEnd())));
+
+ Pair<Double, Double> maxExpansions = new Pair<Double, Double>(
+ pct.getRadiusContextForCreation() - startRadiusFromCreation,
+ pct.getRadiusContextForCreation() - endRadiusFromCreation);
+
+ double currentStartExpansion;
+ double currentEndExpansion;
+
+ // for(Context ctxt:partialNeighborContexts.get(pct)) {
+ for (Context ctxt : contextNeighborsInOneDirection) {
+
+ if (ctxt.getRanges().get(pct).centerDistance(pct.getValue()) < 0) {
+ // End radius
+ currentEndExpansion = ctxt.getRanges().get(pct).distance(ranges.get(pct));
+
+ if (currentEndExpansion < maxExpansions.getB() && currentEndExpansion >= -0.00001) {
+ if (Math.abs(currentEndExpansion) < 0.0001) {
+ currentEndExpansion = 0.0;
+ }
+ maxExpansions.setB(currentEndExpansion);
+ }
+ }
+
+ if (ctxt.getRanges().get(pct).centerDistance(pct.getValue()) > 0) {
+ // Start radius
+ currentStartExpansion = ctxt.getRanges().get(pct).distance(ranges.get(pct));
+
+ if (currentStartExpansion < maxExpansions.getA() && currentStartExpansion >= -0.00001) {
+ if (Math.abs(currentStartExpansion) < 0.0001) {
+ currentEndExpansion = 0.0;
+ }
+ maxExpansions.setA(currentStartExpansion);
+ }
+ }
+ }
+
+ return maxExpansions;
+ }
+
+ // --------------------------------NCS
+ // Resolutions-----------------------------------------
+
+ /**
+ * Solve NC S incompetent head.
+ *
+ * @param head the head
+ */
+ public void solveNCS_IncompetentHead(Head head) {
+ getEnvironment().trace(TRACE_LEVEL.NCS, new ArrayList<String>(Arrays.asList(this.getName(),
+ "*********************************************************************************************************** SOLVE NCS INCOMPETENT HEAD")));
+
+ getEnvironment().raiseNCS(NCS.HEAD_INCOMPETENT);
+ growRanges();
+ getAmas().getHeadAgent().setBadCurrentCriticalityMapping();
+ }
+
+ /**
+ * Solve NC S concurrence.
+ *
+ * @param head the head
+ */
+ public void solveNCS_Concurrence(Head head) {
+ getEnvironment().trace(TRACE_LEVEL.NCS, new ArrayList<String>(Arrays.asList(this.getName(),
+ "*********************************************************************************************************** SOLVE NCS CONCURENCE")));
+
+ getEnvironment().raiseNCS(NCS.CONTEXT_CONCURRENCE);
+ this.shrinkRangesToJoinBorders(head.getBestContext());
+
+ getAmas().getHeadAgent().setBadCurrentCriticalityMapping();
+ }
+
+ /**
+ * Solve NC S uselessness.
+ *
+ * @param head the head
+ */
+ public void solveNCS_Uselessness() {
+ if (!isDying()) {
+ getEnvironment().trace(TRACE_LEVEL.NCS, new ArrayList<String>(Arrays.asList(this.getName(),
+ "*********************************************************************************************************** SOLVE NCS USELESSNESS")));
+ getEnvironment().raiseNCS(NCS.CONTEXT_USELESSNESS);
+ this.destroy();
+ getAmas().getHeadAgent().setBadCurrentCriticalityMapping();
+ }
+
+ }
+
+ public void analyzeResults3(Head head, Context closestContextToOracle) {
+ if (head.getCriticity(this) < head.getErrorAllowed()) {
+ confidence++;
+ } else {
+ if (this != closestContextToOracle) {
+ this.solveNCS_BadPrediction(head);
+ }
+ }
+
+// if (head.getCriticity(this) > head.getErrorAllowed()) {
+//
+//
+// Context betterContext = null;//head.getBetterContext(this,head.getActivatedNeighborsContexts(), getErrorOnAllExperiments());
+//
+// if(betterContext != null) {
+// System.out.println(this.getName() + "<---" + betterContext.getName());
+// this.setModelFromBetterContext(betterContext);
+// world.getScheduler().getHeadAgent().setBadCurrentCriticalityPrediction();
+// }
+// else {
+// System.out.println("OLD COEFS " + localModel.coefsToString());
+// LocalModelAgent newBetterModel = tryNewExperiment();
+//
+// if(tryNewExperiment2()) {
+// System.out.println("NEW COEFS " + localModel.coefsToString());
+// world.getScheduler().getHeadAgent().setBadCurrentCriticalityPrediction();
+// }
+// else {
+// solveNCS_Conflict(head);
+// this.world.getScheduler().addAlteredContext(this);
+// }
+// }
+//
+// }else {
+// System.out.println("OLD COEFS " + localModel.coefsToString());
+// localModel.updateModelWithExperimentAndWeight(getCurrentExperiment(),0.5);
+// System.out.println("NEW COEFS " + localModel.coefsToString());
+// confidence++;
+//
+// }
+
+// mappingCriticality = 0.0;
+// if(head.getActivatedNeighborsContexts().size()>0) {
+// for(Context ctxt : head.getActivatedNeighborsContexts()) {
+// mappingCriticality += this.distance(ctxt);
+// }
+// mappingCriticality /= head.getActivatedNeighborsContexts().size();
+// }
+
+ // NCSDetection_OverMapping();
+
+ }
+
+ public void analyzeResults4(Head head) {
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("------------------------------------------------------------------------------------"
+ + "---------------------------------------- ANALYSE RESULTS " + this.getName())));
+
+ lastDistanceToModel = getLocalModel().distance(this.getCurrentExperiment());
+ lastAverageRegressionPerformanceIndicator = head.getAverageRegressionPerformanceIndicator();
+ if(lastDistanceToModel <= lastAverageRegressionPerformanceIndicator) {
+ //if(getLocalModel().distance(this.getCurrentExperiment()) < head.getAverageRegressionPerformanceIndicator()) {
+ //if (head.getCriticity(this) < head.getErrorAllowed()) {
+ confidence++;
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList(this.getName(), "CONFIDENCE ++")));
+ } else {
+ this.solveNCS_BadPrediction(head);
+ }
+ }
+
+// public double distance(Context ctxt) {
+// double totalDistance = 1.0;
+// double currentDistance = 0.0;
+// int overlaps = 0;
+// int voids = 0;
+//
+// for(Percept pct : world.getScheduler().getPercepts()) {
+// currentDistance = this.distance(ctxt, pct);
+//
+// overlaps += ((currentDistance < 0) ? 1 : 0);
+// voids += ((currentDistance > 0) ? 1 : 0);
+//
+// totalDistance *= currentDistance;
+// }
+//
+// if(overlaps == world.getScheduler().getPercepts().size()) {
+// return - Math.abs(totalDistance);
+// }
+// else if((voids == 1) && (overlaps == world.getScheduler().getPercepts().size()-1)) {
+//
+// }
+// else {
+// return 0;
+// }
+// }
+
+ public Pair<Double, Percept> distance(Context ctxt) {
+ double minDistance = Double.POSITIVE_INFINITY;
+ double maxDistance = Double.NEGATIVE_INFINITY;
+ double currentDistance = 0.0;
+
+ int overlapCounts = 0;
+ Percept voidPercept = null;
+ double voidDistance = 0.0;
+
+ ArrayList<Percept> percepts = getAmas().getPercepts();
+ for (Percept pct : percepts) {
+ currentDistance = this.distance(ctxt, pct);
+ overlapCounts = (currentDistance < 0) ? overlapCounts + 1 : overlapCounts;
+
+ if (currentDistance > 0) {
+ voidPercept = pct;
+ voidDistance = currentDistance / pct.getMinMaxDistance();
+ }
+
+ currentDistance = Math.abs(currentDistance);
+
+ minDistance = Math.min(minDistance, currentDistance / pct.getMinMaxDistance());
+ maxDistance = Math.max(maxDistance, currentDistance / pct.getMinMaxDistance());
+
+ }
+
+ if (overlapCounts == percepts.size()) {
+ return new Pair<Double, Percept>(-minDistance, null);
+ } else if (overlapCounts == (percepts.size() - 1)) {
+ return new Pair<Double, Percept>(voidDistance, voidPercept);
+ } else {
+ return new Pair<Double, Percept>(maxDistance, null);
+ }
+
+ }
+
+
+
+ public HashMap<Percept, Double> boundsToRequest(HashMap<Percept, Pair<Double, Double>> bounds) {
+ HashMap<Percept, Double> request = new HashMap<Percept, Double>();
+
+ for(Percept pct : bounds.keySet()) {
+
+ if(bounds.get(pct) != null) {
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("ENDO REQUESTS BOUNDS", pct.getName(),""+ bounds.get(pct).getA(),""+ bounds.get(pct).getB(), ""+((bounds.get(pct).getB() + bounds.get(pct).getA())/2)) ));
+ request.put(pct, (bounds.get(pct).getB() + bounds.get(pct).getA())/2);
+ }else {
+ getEnvironment().trace(TRACE_LEVEL.ERROR, new ArrayList<String>(Arrays.asList("ENDO REQUESTS ERROR missing percept bounds")));
+ }
+
+
+ }
+
+ return request;
+ }
+
+ public EndogenousRequest endogenousRequest(Context ctxt) {
+
+ HashMap<Percept, Double> voidDistances = new HashMap<Percept, Double>();
+ HashMap<Percept, Double> overlapDistances = new HashMap<Percept, Double>();
+ HashMap<Percept, Pair<Double, Double>> bounds = new HashMap<Percept, Pair<Double, Double>>();
+
+ double currentDistance = 0.0;
+
+ int overlapCounts = 0;
+ for (Percept pct : getAmas().getPercepts()) {
+ currentDistance = this.distance(ctxt, pct);
+
+ if(currentDistance<-pct.getMappingErrorAllowedMin() && getAmas().getCycle()>500) {
+ getEnvironment().trace(TRACE_LEVEL.DEBUG,new ArrayList<String>(Arrays.asList("OVERLAP",pct.getName(), ""+this,""+ctxt)) );
+ overlapCounts+=1;
+ overlapDistances.put(pct, Math.abs(currentDistance));
+ bounds.put(pct, this.overlapBounds(ctxt, pct));
+
+
+ }
+
+
+ if (currentDistance > pct.getMappingErrorAllowedMin() && getAmas().getCycle()>1000) {
+ getEnvironment().trace(TRACE_LEVEL.DEBUG,new ArrayList<String>(Arrays.asList("VOID",pct.getName(), ""+this,""+ctxt, "distance", ""+currentDistance)) );
+ voidDistances.put(pct, currentDistance);
+ bounds.put(pct, this.voidBounds(ctxt, pct));
+ }
+
+
+
+
+
+ }
+
+ if (overlapCounts == getAmas().getPercepts().size() && getAmas().getCycle() > 500) {
+
+ getEnvironment().trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList(getAmas().getPercepts().size() + "OVERLAPS", ""+this,""+ctxt)) );
+
+ HashMap<Percept, Double> request = boundsToRequest(bounds);
+ if(request != null) {
+
+ double currentDistanceToOraclePrediction = this.getLocalModel().distance(this.getCurrentExperiment());
+ double otherContextDistanceToOraclePrediction = ctxt.getLocalModel().distance(ctxt.getCurrentExperiment());
+
+ Double averageDistanceToOraclePrediction = getAmas().getHeadAgent().getAverageRegressionPerformanceIndicator();
+ Double distanceDifference = Math.abs(currentDistanceToOraclePrediction-otherContextDistanceToOraclePrediction);
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>( Arrays.asList(this.getName(),"currentDistanceToOraclePrediction",""+ currentDistanceToOraclePrediction,"otherContextDistanceToOraclePrediction",""+ otherContextDistanceToOraclePrediction, "distanceDifference", ""+distanceDifference)));
+
+ if(distanceDifference<averageDistanceToOraclePrediction) {
+ return new EndogenousRequest(request, bounds, 6, new ArrayList<Context>(Arrays.asList(this,ctxt)), REQUEST.CONCURRENCE);
+ }
+ else {
+ return new EndogenousRequest(request, bounds, 7, new ArrayList<Context>(Arrays.asList(this,ctxt)), REQUEST.CONFLICT);
+ }
+
+
+
+ }
+ }
+ else if(overlapCounts == getAmas().getPercepts().size()-1 && voidDistances.size() == 1 && getAmas().getCycle() > 750) {
+
+ getEnvironment().trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("VOID", ""+this,""+ctxt)) );
+
+ HashMap<Percept, Double> request = boundsToRequest(bounds);
+ if(request != null) {
+
+ if(getAmas().getHeadAgent().isRealVoid(request)) {
+ return new EndogenousRequest(request, bounds, 5, new ArrayList<Context>(Arrays.asList(this,ctxt)), REQUEST.VOID);
+ }
+ }
+ }
+ else {
+ return null;
+ }
+
+ return null;
+ }
+
+ public double distanceAsVolume(Context ctxt) {
+ double totalDistanceAsVolume = 1.0;
+
+ for (Percept pct : getAmas().getPercepts()) {
+ double currentDistance = this.distanceForVolume(ctxt, pct);
+ totalDistanceAsVolume *= currentDistance;
+
+
+ }
+
+ return Math.abs(totalDistanceAsVolume);
+ }
+
+ public double maxDistance(Context ctxt) {
+ double maxDistance = Double.NEGATIVE_INFINITY;
+
+ for (Percept pct : getAmas().getPercepts()) {
+ double currentDistance = this.distanceForMaxOrMin(ctxt, pct) / pct.getMinMaxDistance();
+ if (currentDistance > maxDistance) {
+ maxDistance = currentDistance;
+ }
+
+
+ }
+
+ return maxDistance;
+ }
+
+ public double minDistance(Context ctxt) {
+ double minDistance = Double.POSITIVE_INFINITY;
+
+ for (Percept pct : getAmas().getPercepts()) {
+ minDistance = Math.min(minDistance, this.distanceForMaxOrMin(ctxt, pct) / pct.getMinMaxDistance());
+
+ }
+ return minDistance;
+ }
+
+ public void NCSDetection_BetterNeighbor() {
+ Context closestContextToOracle = this;
+ double minDistanceToOraclePrediction = getLocalModel().distance(this.getCurrentExperiment());
+ double currentDistanceToOraclePrediction = 0.0;
+
+ for (Context ctxt : getAmas().getHeadAgent().getActivatedNeighborsContexts()) {
+
+ if (ctxt != this) {
+ currentDistanceToOraclePrediction = ctxt.getLocalModel().distance(this.getCurrentExperiment());
+ if (currentDistanceToOraclePrediction < minDistanceToOraclePrediction) {
+ minDistanceToOraclePrediction = currentDistanceToOraclePrediction;
+ closestContextToOracle = ctxt;
+ }
+ }
+
+ }
+
+ if (closestContextToOracle != this) {
+ solveNCS_BetterNeighbor(closestContextToOracle);
+ }
+
+ }
+
+ public void solveNCS_BetterNeighbor(Context betterContext) {
+ getEnvironment().trace(TRACE_LEVEL.NCS, new ArrayList<String>(Arrays.asList(this.getName(), betterContext.getName(),
+ "*********************************************************************************************************** SOLVE NCS BETTER NEIGHBOR")));
+ localModel = new LocalModelMillerRegression(this, betterContext.getLocalModel().getCoef(),
+ betterContext.getLocalModel().getFirstExperiments());
+ }
+
+ public void NCSDetection_OverMapping() {
+
+
+
+
+ for(Context ctxt : getAmas().getHeadAgent().getActivatedNeighborsContexts()) {
+
+
+ if(ctxt != this && !ctxt.isDying()) {
+
+
+
+ double currentDistanceToOraclePrediction = this.getLocalModel().distance(this.getCurrentExperiment());
+ double otherContextDistanceToOraclePrediction = ctxt.getLocalModel().distance(ctxt.getCurrentExperiment());
+
+ //double minDistanceToOraclePrediction = Math.min(getAmas().getHeadAgent().getDistanceToRegressionAllowed(), getAmas().getHeadAgent().getDistanceToRegressionAllowed());
+ Double averageDistanceToOraclePrediction = getAmas().getHeadAgent().getAverageRegressionPerformanceIndicator();
+ Double distanceDifference = Math.abs(currentDistanceToOraclePrediction-otherContextDistanceToOraclePrediction);
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>( Arrays.asList(this.getName(),"currentDistanceToOraclePrediction",""+ currentDistanceToOraclePrediction,"otherContextDistanceToOraclePrediction",""+ otherContextDistanceToOraclePrediction, "distanceDifference", ""+distanceDifference)));
+
+ if(distanceDifference<averageDistanceToOraclePrediction) {
+
+
+
+
+ for(Percept pct : ranges.keySet()) {
+
+ boolean fusionTest = true;
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList(this.getName(),ctxt.getName(),pct.getName(), ""+Math.abs(this.distance(ctxt, pct)), "DISTANCE", "" + getEnvironment().getMappingErrorAllowed())));
+ if(Math.abs(this.distance(ctxt, pct)) < pct.getMappingErrorAllowedOverMapping()){
+
+ for(Percept otherPct : ranges.keySet()) {
+
+ if(otherPct != pct) {
+
+ double lengthDifference = Math.abs(ranges.get(otherPct).getLenght() - ctxt.getRanges().get(otherPct).getLenght());
+ double centerDifference = Math.abs(ranges.get(otherPct).getCenter() - ctxt.getRanges().get(otherPct).getCenter());
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList(this.getName(),ctxt.getName(),otherPct.getName(), ""+lengthDifference,""+centerDifference, "LENGTH & CENTER DIFF", "" + getEnvironment().getMappingErrorAllowed())));
+ fusionTest = fusionTest && (lengthDifference < otherPct.getMappingErrorAllowedOverMapping()) && (centerDifference< otherPct.getMappingErrorAllowedOverMapping());
+ }
+ }
+
+ if(fusionTest) {
+ solveNCS_OverMapping(ctxt);
+ }
+
+ }
+ }
+
+ }
+
+ }
+ }
+
+ }
+
+ private void solveNCS_OverMapping(Context fusionContext) {
+ getEnvironment().trace(TRACE_LEVEL.NCS, new ArrayList<String>(Arrays.asList(this.getName(),
+ "*********************************************************************************************************** SOLVE NCS OVERMAPPING")));
+ getEnvironment().raiseNCS(NCS.CONTEXT_OVERMAPPING);
+
+
+ for(Percept pct : getAmas().getPercepts()) {
+ this.getRanges().get(pct).setEnd(Math.max(this.getRanges().get(pct).getEnd(), fusionContext.getRanges().get(pct).getEnd()));
+ this.getRanges().get(pct).setStart(Math.min(this.getRanges().get(pct).getStart(), fusionContext.getRanges().get(pct).getStart()));
+ }
+
+ this.setConfidence(Math.max(this.getConfidence(), fusionContext.getConfidence()));
+ regressionPerformance.setPerformanceIndicator(Math.max(this.regressionPerformance.getPerformanceIndicator(), fusionContext.regressionPerformance.getPerformanceIndicator()));
+
+
+ fusionContext.destroy();
+ getAmas().getHeadAgent().setBadCurrentCriticalityMapping();
+ }
+
+ public void solveNCS_ChildContext() {
+ HashMap<Percept, Double> request = new HashMap<Percept, Double>();
+ for(Percept pct : getAmas().getPercepts()) {
+ request.put(pct, getRandomValueInRange(pct));
+ }
+ getEnvironment().trace(TRACE_LEVEL.EVENT,new ArrayList<String>(Arrays.asList("NEW ENDO REQUEST","10", ""+request, ""+this.getName())));
+ getAmas().getHeadAgent().addSelfRequest(request, 10,this);
+ }
+
+ private Double getRandomValueInRange(Percept pct) {
+ return ranges.get(pct).getStart() + ranges.get(pct).getLenght()*Math.random();
+ }
+
+ public Experiment getCurrentExperiment() {
+ ArrayList<Percept> percepts = getAmas().getPercepts();
+ Experiment exp = new Experiment(this);
+ for (Percept pct : percepts) {
+ exp.addDimension(pct, pct.getValue());
+ }
+ exp.setOracleProposition(getAmas().getHeadAgent().getOracleValue());
+
+ return exp;
+ }
+
+ public double sumOfRangesLengths() {
+ double sum = 0;
+
+ for (Percept pct : getAmas().getPercepts()) {
+ sum += this.getRanges().get(pct).getLenght();
+ }
+
+ return sum;
+ }
+
+ public double rangeLengthRatio(Percept pct) {
+ return this.getRanges().get(pct).getLenght() / sumOfRangesLengths();
+ }
+
+ public Pair<Boolean, Double> tryAlternativeModel(LocalModel alternativeModel) {
+ boolean betterModelTest = true;
+ double sumError = 0.0;
+
+ return new Pair<Boolean, Double>(betterModelTest, sumError);
+ }
+
+ public void solveNCS_BadPrediction(Head head) {
+ getEnvironment().trace(TRACE_LEVEL.NCS, new ArrayList<String>(Arrays.asList(this.getName(),
+ "*********************************************************************************************************** SOLVE NCS CONFLICT")));
+ getEnvironment().raiseNCS(NCS.CONTEXT_CONFLICT_FALSE);
+
+ if (head.getNewContext() == this) {
+ head.setNewContext(null);
+ }
+ ;
+
+ confidence -= 2;
+ getAmas().getHeadAgent().setBadCurrentCriticalityConfidence();
+ getAmas().getHeadAgent().setBadCurrentCriticalityPrediction();
+
+ ArrayList<Percept> percepts = new ArrayList<Percept>();
+ percepts.addAll(ranges.keySet());
+
+ Pair<Percept, Context> perceptForAdapatationAndOverlapingContext = getPerceptForAdaptationWithOverlapingContext(
+ percepts);
+ Percept p = perceptForAdapatationAndOverlapingContext.getA();
+
+// if(perceptForAdapatationAndOverlapingContext.getB()!=null) {
+// world.trace(new ArrayList<String>(Arrays.asList(this.getName(),p.getName(),perceptForAdapatationAndOverlapingContext.getB().getName(), "*********************************************************************************************************** CONFLICT OVERLAP")));
+// Range overlapingRange = perceptForAdapatationAndOverlapingContext.getB().getRanges().get(p);
+//
+//
+// if (Math.abs(overlapingRange.getStart() - this.getRanges().get(p).getEnd()) >= Math.abs(overlapingRange.getEnd() - this.getRanges().get(p).getStart())) {
+//
+// this.getRanges().get(p).adaptOnOverlap(overlapingRange, overlapingRange.getEnd());
+// } else {
+// this.getRanges().get(p).adaptOnOverlap(overlapingRange, overlapingRange.getStart());
+// }
+//
+// //ranges.get(p).adapt(p.getValue(), Math.abs(this.distance(overlapingContext, p)));
+//
+// }else {
+// ranges.get(p).adapt(p.getValue());
+// }
+
+ ranges.get(p).adapt(p.getValue());
+
+// if(perceptForAdapatationAndOverlapingContext.getB()!=null) {
+// if(testIfOtherContextShouldFinalyShrink(perceptForAdapatationAndOverlapingContext.getB(), perceptForAdapatationAndOverlapingContext.getA())){
+// perceptForAdapatationAndOverlapingContext.getB().getRanges().get(p).adapt(p.getValue());
+// }
+// }
+
+// if (head.isContextFromPropositionWasSelected() && head.getCriticity() <= head.getErrorAllowed()){
+//
+// //System.out.println("$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$");
+//
+// p = this.getPerceptWithLesserImpactOnVolumeNotIncludedIn2(percepts, head.getBestContext());
+//
+// if (p == null) {
+// this.die();
+// }else {
+// ranges.get(p).adaptTowardsBorder(head.getBestContext());
+// }
+// } else {
+// p = this.getPerceptWithLesserImpactOnVolume2(percepts);
+// ranges.get(p).adapt(p.getValue());
+// }
+
+// for (Percept v : ranges.keySet()) {
+// if (ranges.get(v).isTooSmall()){
+// solveNCS_Uselessness();
+// break;
+// }
+// }
+ getAmas().getHeadAgent().setBadCurrentCriticalityMapping();
+ }
+
+ public void updateAVT() {
+ for (Percept p : ranges.keySet()) {
+ if (ranges.get(p).getLastEndTickModification() != getAmas().getCycle()) {
+ ranges.get(p).endogenousAdaptEndUsingAVT();
+ }
+ if (ranges.get(p).getLastStartTickModification() != getAmas().getCycle()) {
+ ranges.get(p).endogenousAdaptStartUsingAVT();
+ }
+ }
+ }
+
+ private Percept getPerceptWithBiggerImpactOnOverlap(ArrayList<Percept> percepts, Context bestContext) {
+ Percept perceptWithBiggerImpact = null;
+ double volumeLost = Double.MAX_VALUE;
+ double vol = 1.0;
- List<Percept> percepts = getAmas().getPercepts();
for (Percept percept : percepts) {
- double length = Math.abs(percept.getMinMaxDistance()) / 4.0;
- Range range = new Range(this, percept.getValue() - length, percept.getValue() + length, 0, true, true,
- percept);
- ranges.put(percept, range);
- firstPoint.addDimension(percept, percept.getValue());
+ if (!ranges.get(percept).isPerceptEnum()) {
+ Range bestContextRanges = bestContext.getRanges().get(percept);
+
+ if (!(bestContextRanges.getStart() <= ranges.get(percept).getStart()
+ && ranges.get(percept).getEnd() <= bestContextRanges.getEnd())) {
+
+ if (percept.contextOrder(this, bestContext)) {
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList("ORDER :", percept.getName(), this.getName(), bestContext.getName())));
+ vol = Math.abs(
+ percept.getEndRangeProjection(this) - percept.getStartRangeProjection(bestContext));
+ if (vol < volumeLost) {
+ volumeLost = vol;
+ perceptWithBiggerImpact = percept;
+ }
+ } else if (percept.contextOrder(bestContext, this)) {
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList("ORDER :", percept.getName(), bestContext.getName(), this.getName())));
+ vol = Math.abs(
+ percept.getEndRangeProjection(bestContext) - percept.getStartRangeProjection(this));
+ if (vol < volumeLost) {
+ volumeLost = vol;
+ perceptWithBiggerImpact = percept;
+ }
+ } else if (percept.contextIncludedIn(bestContext, this)) {
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("INCLUSION :", percept.getName(),
+ bestContext.getName(), this.getName())));
+ vol = Math.abs(percept.getEndRangeProjection(bestContext)
+ - percept.getStartRangeProjection(bestContext));
+ if (vol < volumeLost) {
+ volumeLost = vol;
+ perceptWithBiggerImpact = percept;
+ }
+ }
+ }
+ }
+ }
+ return perceptWithBiggerImpact;
+ }
+
+ public double getOverlappingVolume(Context overlappingCtxt) {
+ double volume = 1.0;
+ for (Percept pct : ranges.keySet()) {
+ volume *= this.getRanges().get(pct).overlapDistance(overlappingCtxt.getRanges().get(pct));
+ }
+ return volume;
+ }
+
+ private Pair<Percept, Context> getPerceptForAdaptationWithOverlapingContext(ArrayList<Percept> percepts) {
+ Percept perceptForAdapation = null;
+ Context overlapingContext = null;
+ double minDistanceToFrontier = Double.MAX_VALUE;
+ double distanceToFrontier;
+ double maxOverlappingVolume = Double.NEGATIVE_INFINITY;
+ double overlappingVolume;
+
+ if (getAmas().getHeadAgent().getActivatedContexts().size() > 1) {
+
+ for (Context ctxt : getAmas().getHeadAgent().getActivatedContexts()) {
+ if (ctxt != this) {
+ if (this.containedBy(ctxt)) {
+ this.destroy();
+ } else {
+ overlappingVolume = this.getOverlappingVolume(ctxt);
+ if (overlappingVolume > maxOverlappingVolume) {
+ perceptForAdapation = getPerceptWithBiggerImpactOnOverlap(percepts, ctxt);
+ overlapingContext = ctxt;
+ }
+ }
+ }
+ }
+ }
+ if (perceptForAdapation == null) {
+ for (Percept pct : percepts) {
+ if (!ranges.get(pct).isPerceptEnum()) {
+
+ distanceToFrontier = Math.min(ranges.get(pct).startDistance(pct.getValue()),
+ ranges.get(pct).endDistance(pct.getValue()));
+
+ if (distanceToFrontier < minDistanceToFrontier) {
+ minDistanceToFrontier = distanceToFrontier;
+ perceptForAdapation = pct;
+ }
+ }
+ }
+ }
+
+ return new Pair<Percept, Context>(perceptForAdapation, overlapingContext);
+ }
+
+ public boolean containedBy(Context ctxt) {
+ boolean contained = true;
+
+ for (Percept pct : ranges.keySet()) {
+
+ contained = contained && ranges.get(pct).containedBy(ctxt.getRanges().get(pct));
+ }
+
+ return contained;
+ }
+
+ /**
+ * Sets the ranges.
+ *
+ * @param ranges the ranges
+ */
+ public void setRanges(HashMap<Percept, Range> ranges) {
+ this.ranges = ranges;
+ }
+
+ /**
+ * Gets the controler.
+ *
+ * @return the controler
+ */
+ public Head getControler() {
+ return getAmas().getHeadAgent();
+ }
+
+ /**
+ * Gets the action.
+ *
+ * @return the action
+ */
+ public double getAction() {
+ return action;
+ }
+
+ /**
+ * Sets the action.
+ *
+ * @param action the new action
+ */
+ public void setAction(double action) {
+ this.action = action;
+ }
+
+ // -----------------------------------------------------------------------------------------------
+
+ public double getNormalizedConfidence() {
+ return 1 / (1 + Math.exp(-confidence));
+ // return getParametrizedNormalizedConfidence(20.0);
+ }
+
+ public double getParametrizedNormalizedConfidence(double dispersion) {
+ return 1 / (1 + Math.exp(-confidence / dispersion));
+ }
+
+ public double getInfluenceWithConfidence(HashMap<Percept, Double> situation) {
+ Double influence = 1.0;
+
+ for (Percept pct : situation.keySet()) {
+
+ influence *= getInfluenceByPerceptSituationWithConfidence(pct, situation.get(pct));
+ }
+
+ return influence;
+ }
+
+ public double getInfluenceWithConfidenceAndVolume(HashMap<Percept, Double> situation) {
+ return getVolume() * getInfluenceWithConfidence(situation);
+ }
+
+ public double getInfluence(HashMap<Percept, Double> situation) {
+ Double influence = 1.0;
+
+ for (Percept pct : situation.keySet()) {
+
+ influence *= getInfluenceByPerceptSituation(pct, situation.get(pct));
+ }
+
+ return influence;
+ }
+
+ public double getWorstInfluenceWithConfidence(HashMap<Percept, Double> situation) {
+ Double worstInfluence = Double.POSITIVE_INFINITY;
+ Double currentInfluence = 0.0;
+
+ for (Percept pct : situation.keySet()) {
+
+ currentInfluence = getInfluenceByPerceptSituationWithConfidence(pct, situation.get(pct));
+ if (currentInfluence < worstInfluence) {
+ worstInfluence = currentInfluence;
+ }
+ }
+
+ return worstInfluence;
+ }
+
+ public double getWorstInfluence(HashMap<Percept, Double> situation) {
+ Double worstInfluence = Double.POSITIVE_INFINITY;
+ Double currentInfluence = 0.0;
+
+ for (Percept pct : situation.keySet()) {
+
+ currentInfluence = getInfluenceByPerceptSituation(pct, situation.get(pct));
+ if (currentInfluence < worstInfluence) {
+ worstInfluence = currentInfluence;
+ }
+ }
+
+ return worstInfluence;
+ }
+
+ public double getWorstInfluenceWithVolume(HashMap<Percept, Double> situation) {
+
+ return getVolume() * getWorstInfluence(situation);
+ }
+
+ public double getWorstInfluenceWithWorstRange(HashMap<Percept, Double> situation) {
+
+ return getWorstRange() * getWorstInfluence(situation);
+ }
+
+ public double getInfluenceByPerceptSituation(Percept pct, double situation) {
+ double center = getCenterByPercept(pct);
+ double radius = getRadiusByPercept(pct);
+
+ return Math.exp(-((situation - center)*(situation - center)) / (2 * (radius*radius)));
+ }
+
+ public double getInfluenceByPerceptSituationWithConfidence(Percept pct, double situation) {
+
+ return getNormalizedConfidence() * getInfluenceByPerceptSituation(pct, situation);
+ }
+
+ public double getVolume() {
+ double volume = 1.0;
+
+ for (Percept pct : getRanges().keySet()) {
+ volume *= 2 * getRadiusByPercept(pct);
+ }
+ return volume;
+ }
+
+ public double getWorstRange() {
+ Double volume = Double.POSITIVE_INFINITY;
+
+ for (Percept pct : getRanges().keySet()) {
+ // volume *= 2*getRadiusByPercept(pct);
+ if (getRadiusByPercept(pct) < volume) {
+ volume = getRadiusByPercept(pct);
+ }
+ }
+ return volume;
+ }
+
+ /**
+ * Analyze results.
+ *
+ * @param head the head
+ */
+ public void analyzeResults(Head head) {
+ if (head.getCriticity(this) > head.getErrorAllowed()) {
+ solveNCS_BadPrediction(head);
+ getAmas().addAlteredContext(this);
+ } else {
+// if (head.getCriticity(this) > head.getInexactAllowed()) {
+// solveNCS_ConflictInexact(head);
+// }
+// else {
+// confidence++;
+// //confidence = confidence * 2;
+// }
+ }
+ }
+
+ /**
+ * Grow every ranges allowing to includes current situation.
+ *
+ * @param head the head
+ */
+ public void growRanges() {
+
+ ArrayList<Percept> allPercepts = getAmas().getPercepts();
+ for (Percept pct : allPercepts) {
+ boolean contain = ranges.get(pct).contains(pct.getValue()) == 0 ;
+
+ if (!contain) {
+ if(ranges.get(pct).getLenght()<pct.getMappingErrorAllowedMax()) {
+ ranges.get(pct).adapt(pct.getValue());
+ }
+
+ //ranges.get(pct).extend(pct.getValue(), pct);
+ //world.getScheduler().getHeadAgent().NCSMemories.add(new NCSMemory(world, new ArrayList<Context>(),"Grow Range "+ pct.getName()));
+ }
}
- firstPoint.setProposition(getAmas().getHeads().get(0).getOracleValue());
- experiments.add(firstPoint);
- localModel = getAmas().buildLocalModel(this);
- buildModel(getAmas(), head, amoeba.getPercepts());
}
/**
- * Constructor used to create a new Context when loading a file (in Save State
- * class)
- *
- * @param amoeba the main amas
- * @param head
- * @param name
- * @param starts
- * @param ends
- * @param experiments
- * @param localModel
- * @param confidence
+ * Shrink ranges to join borders.
+ *
+ * @param head the head
+ * @param c the c
*/
- public Context(AMOEBA amoeba, Head head, String name, Map<Percept, Double> starts, Map<Percept, Double> ends,
- ArrayList<Experiment> experiments, LocalModel localModel, double confidence) {
- super(amoeba);
- this.ranges = new HashMap<>();
- this.experiments = experiments;
- this.confidence = confidence;
- this.localModel = localModel;
+ public void shrinkRangesToJoinBorders(Context bestContext) {
+ Percept perceptWithBiggerImpactOnOverlap = getPerceptWithBiggerImpactOnOverlap(getAmas().getPercepts(),
+ bestContext);
- setName(name);
- List<Percept> percepts = new ArrayList<>(starts.keySet());
- for (Percept percept : percepts) {
- Range range = new Range(this, starts.get(percept), ends.get(percept), 0, true, true, percept);
- this.ranges.put(percept, range);
- }
+ if (perceptWithBiggerImpactOnOverlap == null) {
+ this.destroy();
+ } else {
- buildModel(amoeba, head, percepts);
- }
-
- @Override
- protected void onInitialization() {
- super.onInitialization();
- ranges = new HashMap<Percept, Range>();
- experiments = new ArrayList<Experiment>();
- setName(String.valueOf(this.hashCode()));
- }
- private final void buildModel(AMOEBA amoeba, Head head, List<Percept> percepts) {
- this.headAgent = head;
- this.localModel.updateModel(this);
+ ranges.get(perceptWithBiggerImpactOnOverlap).adapt(perceptWithBiggerImpactOnOverlap.getValue());
- for (Percept percept : percepts) {
- percept.addContextProjection(this);
}
}
- @Override
- protected void onAct() {
+ private double distance(Context ctxt, Percept pct) {
+ return this.getRanges().get(pct).distance(ctxt.getRanges().get(pct));
+ }
+
+ private Pair<Double,Double> overlapBounds(Context ctxt, Percept pct) {
+
- if(amas.getValidContexts().contains(this)) {
- logger().debug("CYCLE "+getAmas().getCycle(), "Context %s sent proposition %f", getName(), getActionProposal());
- activations++;
- headAgent.proposition(this);
+ if (pct.contextIncludedIn(this, ctxt)) {
+
+ return new Pair<Double, Double>(this.getRanges().get(pct).getStart(), this.getRanges().get(pct).getEnd());
+
+ } else if (pct.contextIncludedIn(ctxt, this)) {
+
+ return new Pair<Double, Double>(ctxt.getRanges().get(pct).getStart(), ctxt.getRanges().get(pct).getEnd());
+
+ } else if (pct.contextOrder(this, ctxt)) {
+
+ return new Pair<Double, Double>(ctxt.getRanges().get(pct).getStart(), this.getRanges().get(pct).getEnd());
+
+ } else if (pct.contextOrder(ctxt, this)) {
+
+ return new Pair<Double, Double>(this.getRanges().get(pct).getStart(), ctxt.getRanges().get(pct).getEnd());
+
+ } else {
+
+ return null;
}
- // Kill small contexts
- for (Percept percept : ranges.keySet()) {
- if (ranges.get(percept).isTooSmall()) {
- solveNCS_Uselessness(headAgent);
- break;
- }
- }
+
}
- @Override
- protected void onRenderingInitialization() {
- try {
- Constructor<? extends RenderStrategy> constructor = defaultRenderStrategy.getConstructor(Object.class);
- setRenderStrategy(constructor.newInstance(this));
- } catch (InstantiationException | IllegalAccessException | NoSuchMethodException | SecurityException | IllegalArgumentException | InvocationTargetException e) {
- e.printStackTrace();
- }
- super.onRenderingInitialization();
- }
+ private Pair<Double,Double> voidBounds(Context ctxt, Percept pct) {
- // ---------------------------- NCS Resolutions ----------------------------
-
- public void solveNCS_IncompetentHead(Head head) {
- amas.getEnvironment().raiseNCS(NCS.HEAD_INCOMPETENT);
- growRanges();
- }
+
+
+ if(this.getRanges().get(pct).getEnd() < ctxt.getRanges().get(pct).getStart()) {
+ return new Pair<Double, Double>(this.getRanges().get(pct).getEnd(), ctxt.getRanges().get(pct).getStart());
+ }
+ else {
+ return new Pair<Double, Double>(ctxt.getRanges().get(pct).getEnd(), this.getRanges().get(pct).getStart());
+ }
+
- public void solveNCS_Concurrence(Head head) {
- amas.getEnvironment().raiseNCS(NCS.CONTEXT_CONCURRENCE);
- this.shrinkRangesToJoinBorders(head.getBestContext());
+
}
- private void solveNCS_Uselessness(Head head) {
- amas.getEnvironment().raiseNCS(NCS.CONTEXT_USELESSNESS);
- this.destroy();
+ private double distanceForVolume(Context ctxt, Percept pct) {
+ return this.getRanges().get(pct).distanceForVolume(ctxt.getRanges().get(pct));
}
- private void solveNCS_ConflictInexact(Head head) {
- amas.getEnvironment().raiseNCS(NCS.CONTEXT_CONFLICT_INEXACT);
- confidence--;
- updateExperiments();
+ private double distanceForMaxOrMin(Context ctxt, Percept pct) {
+ return Math.abs(this.getRanges().get(pct).distanceForMaxOrMin(ctxt.getRanges().get(pct)));
}
- private void solveNCS_Conflict(Head head) {
+ public Context getNearestContextBySortedPerceptAndRange(HashMap<String, ArrayList<Context>> sortedPossibleNeigbours,
+ Percept percept, String range) {
+ int indexOfCurrentContext = sortedPossibleNeigbours.get(range).indexOf(this);
- amas.getEnvironment().raiseNCS(NCS.CONTEXT_CONFLICT_FALSE);
+ if (sortedPossibleNeigbours.get(range).size() > 1) {
- if (head.getNewContext() == this) {
- head.setNewContext(null);
- }
- ;
+ if ((indexOfCurrentContext > 0)
+ && (indexOfCurrentContext < sortedPossibleNeigbours.get(range).size() - 1)) {
+ if (range.equals("start")) {
+ return sortedPossibleNeigbours.get(range).get(indexOfCurrentContext + 1);
+ } else if (range.equals("end")) {
+ return sortedPossibleNeigbours.get(range).get(indexOfCurrentContext - 1);
+ } else {
+ return null;
+ }
+ }
- // The conflict lowers confidence
- confidence -= 2;
+ else if (indexOfCurrentContext == 0) {
+ if (range.equals("start")) {
+ return sortedPossibleNeigbours.get(range).get(indexOfCurrentContext + 1);
+ } else {
+ return null;
+ }
+ }
- ArrayList<Percept> percepts = new ArrayList<Percept>();
- percepts.addAll(ranges.keySet());
+ else if (indexOfCurrentContext == sortedPossibleNeigbours.get(range).size() - 1) {
+ if (range.equals("end")) {
+ return sortedPossibleNeigbours.get(range).get(indexOfCurrentContext - 1);
+ } else {
+ return null;
+ }
+ }
- if (head.isContextFromPropositionWasSelected() && head.getCriticity() <= head.getErrorAllowed()) {
- Percept percept = this.getPerceptsWithLesserImpactOnVolumeNotIncludedIn(percepts, head.getBestContext());
- if (percept == null) {
- this.destroy();
- } else {
- ranges.get(percept).matchBorderWith(head.getBestContext());
+ else {
+ return null;
}
+
} else {
- Percept percept = this.getPerceptsWithLesserImpactOnVolume(percepts);
- ranges.get(percept).adapt(this, percept.getValue(), percept);
+ return null;
}
+ }
- for (Percept percept : percepts) {
- if (ranges.get(percept).isTooSmall()) {
- solveNCS_Uselessness(head);
+ public double distance(Percept pct, double value) {
+ return this.ranges.get(pct).distance(value);
+ }
+
+ public void NCSDetection_Uselessness() {
+ for (Percept v : ranges.keySet()) {
+ if (ranges.get(v).isTooSmall()) {
+ solveNCS_Uselessness();
break;
}
}
+// if(!isDying) {
+// for(Context ctxt : world.getScheduler().getHeadAgent().getActivatedNeighborsContexts()) {
+// if(ctxt != this) {
+// if(this.getConfidence()<=ctxt.getConfidence()) {
+// if(this.containedBy(ctxt)) {
+// solveNCS_Uselessness();
+// break;
+// }
+// }
+// }
+// }
+// }
}
- // -----------------------------------------------------------------------------------------------
+ @Override
+ protected void onAct() {
+
+ onActOpitmized();
+ //onActOld();
+
+ }
+
+ private void onActOpitmized() {
+ if(amas.getValidContexts().contains(this)) {
+ logger().debug("CYCLE "+getAmas().getCycle(), "Context %s sent proposition %f", getName(), getActionProposal());
+ activations++;
+ getAmas().getHeadAgent().proposition(this);
+ }
+ }
+
+ /**
+ * Sets the confidence.
+ *
+ * @param confidence the new confidence
+ */
+ public void setConfidence(double confidence) {
+ this.confidence = confidence;
+ }
+
+ @Override
+ protected void onInitialization() {
+ super.onInitialization();
+ ranges = new HashMap<Percept, Range>();
+ setName(String.valueOf(this.hashCode()));
+ }
+
+ @Override
+ protected void onRenderingInitialization() {
+ try {
+ Constructor<? extends RenderStrategy> constructor = defaultRenderStrategy.getConstructor(Object.class);
+ setRenderStrategy(constructor.newInstance(this));
+ } catch (InstantiationException | IllegalAccessException | NoSuchMethodException | SecurityException
+ | IllegalArgumentException | InvocationTargetException e) {
+ e.printStackTrace();
+ }
+ super.onRenderingInitialization();
+ }
public String toString() {
return "Context :" + this.getName();
}
+
+ public String toStringPierre() {
+ String s = "";
+ s += "Context : " + getName() + "\n";
+ s += "Model : ";
+ s += this.localModel.getCoefsFormula() + "\n";
+ s += "Max Prediction " + getLocalModel().getMaxProposition() + "\n";
+ s += "Min Prediction " + getLocalModel().getMinProposition() + "\n";
+ return s;
+ }
+
+ public ArrayList<String> toStringArrayPierre() {
+ ArrayList<String> array = new ArrayList<String>();
+ array.add(getName());
+ array.add(""+localModel.getCoef()[0] );
+ for(int i =1;i<localModel.getCoef().length;i++) {
+ array.add(""+localModel.getCoef()[i]);
+ }
+ array.add(""+ getLocalModel().getMinProposition());
+ array.add(""+ getLocalModel().getMaxProposition());
+
+ return array;
+ }
public String toStringFull() {
String s = "";
s += "Context : " + getName() + "\n";
+ s += "creation tick : " + tickCreation +"\n";
s += "\n";
-
+
s += "Model : ";
s += this.localModel.getCoefsFormula() + "\n";
+
s += "\n";
- s += "Number of activations : " + activations + "\n";
- s += "Action proposed : " + this.getActionProposal() + "\n";
- s += "Number of experiments : " + experiments.size() + "\n";
- s += "Confidence : " + confidence + "\n";
- s += "Local model : " + localModel.getFormula(this) + "\n";
+ s += "Last Distance to Regression " + lastDistanceToModel + "\n";
+ s += "Last Average Distance To Regression Allowed " + lastAverageRegressionPerformanceIndicator +"\n";
+ s += "Mean Distance To Regression " + criticalities.getCriticalityMean("distanceToRegression") + "\n";
+ s += "Distance To Regression Allowed " + regressionPerformance.getPerformanceIndicator() +"\n\n";
- s += "\n";
- s += "Possible neighbours : \n";
+ s += "Max Prediction " + getLocalModel().getMaxProposition() + "\n";
+ s += "Min Prediction " + getLocalModel().getMinProposition() + "\n\n";
- return s;
- }
-
- private void updateExperiments() {
- ArrayList<Percept> var = amas.getPercepts();
- Experiment exp = new Experiment();
- for (Percept v : var) {
- exp.addDimension(v, v.getValue());
+ s += "ASKED REQUEST " + waitingRequests.size() + "\n";
+ for(EndogenousRequest rqt : waitingRequests) {
+ s += rqt + "\n";
}
- exp.setProposition(headAgent.getOracleValue());
-
- experiments.add(exp);
- localModel.updateModel(this);
- }
-
- public void analyzeResults(Head head) {
- if (head.getCriticity(this) > head.getErrorAllowed()) {
- solveNCS_Conflict(head);
-
+ s += "\n";
+ s += "Number of activations : " + activations + "\n";
+ s += "Number of selection : " + nSelection +"\n";
+ if (actionProposition != null) {
+ s += "Action proposed : " + this.actionProposition + "\n";
} else {
- if (head.getCriticity(this) > head.getInexactAllowed()) {
- solveNCS_ConflictInexact(head);
- } else {
- confidence++;
- }
+ s += "Action proposed : " + this.getActionProposal() + "\n";
}
- }
+ s += "Confidence : " + confidence + "\n";
- /**
- * Grow every ranges allowing to includes current situation.
- *
- */
- public void growRanges() {
- ArrayList<Percept> percepts = amas.getPercepts();
- for (Percept percept : percepts) {
- boolean contain = ranges.get(percept).contains(percept.getValue()) == 0 ? true : false;
- if (!contain) {
- ranges.get(percept).adapt(this, percept.getValue(), percept);
- }
- }
+ s += "\n";
+
+ return s;
}
- public void shrinkRangesToJoinBorders(Context consideredContext) {
- Set<Percept> percetList = ranges.keySet();
- ArrayList<Percept> containingRanges = new ArrayList<Percept>();
+ public String toStringReducted(HashMap<Percept, Double> situation) {
+ String s = "";
+ s += "Context : " + getName() + "\n";
+ s += "Model : ";
+ s += this.localModel.getCoefsFormula() + "\n";
+ ;
+
+ for (Percept v : ranges.keySet()) {
+ s += v.getName() + " : " + ranges.get(v).toString() + "\n";
- for (Percept percept : percetList) {
- boolean contain = ranges.get(percept).contains(percept.getValue()) == 0 ? true : false;
- if (contain) {
- containingRanges.add(percept);
- }
}
- Percept perceptWithLesserImpact = getPerceptsWithLesserImpactOnVolumeNotIncludedIn(containingRanges,
- consideredContext);
- if (perceptWithLesserImpact == null) {
- this.destroy();
+ s += "Number of activations : " + activations + "\n";
+ if (actionProposition != null) {
+ s += "Action proposed : " + this.actionProposition + "\n";
} else {
- ranges.get(perceptWithLesserImpact).matchBorderWith(consideredContext);
+ s += "Action proposed : " + this.getActionProposal() + "\n";
}
+ s += "Confidence : " + confidence + "\n";
+ s += "Normalized confidence : " + getNormalizedConfidence() + "\n";
+ s += "Influence :" + getInfluence(situation) + "\n";
+ s += "Worst Influence :" + getWorstInfluence(situation) + "\n";
+ s += "Worst Influence + Conf :" + getWorstInfluenceWithConfidence(situation) + "\n";
+ s += "Worst Influence + Vol :" + getWorstInfluenceWithVolume(situation) + "\n";
+ for (Percept pct : situation.keySet()) {
+ s += "Influence " + pct.getName() + " : " + getInfluenceByPerceptSituation(pct, situation.get(pct)) + "\n";
+ }
+ s += "Global Influence * Confidence :" + getInfluenceWithConfidence(situation) + "\n";
+ for (Percept pct : situation.keySet()) {
+ s += "Influence * Confidence " + pct.getName() + " : "
+ + getInfluenceByPerceptSituationWithConfidence(pct, situation.get(pct)) + "\n";
+ }
+
+ s += "\n";
+
+ return s;
}
@Override
public void destroy() {
- ArrayList<Percept> percepts = amas.getPercepts();
- for (Percept percept : percepts) {
+ getEnvironment().trace(TRACE_LEVEL.EVENT, new ArrayList<String>(
+ Arrays.asList("-----------------------------------------", this.getName(), "DIE")));
+
+ getAmas().addToKillContextForUnityUI(this);
+
+ for (Percept percept : getAmas().getPercepts()) {
percept.deleteContextProjection(this);
}
+
super.destroy();
}
public double getActionProposal() {
- return localModel.getProposition(this);
+ return localModel.getProposition();
}
public double getCenterByPercept(Percept pct) {
- return (this.getRangeByPerceptName(pct.getName()).getEnd()
- + this.getRangeByPerceptName(pct.getName()).getStart()) / 2;
+ Range rangeByPercept = this.getRangeByPercept(pct);
+ return (rangeByPercept.getEnd()
+ + rangeByPercept.getStart()) / 2;
}
public double getConfidence() {
return confidence;
}
- public ArrayList<Experiment> getExperiments() {
- return experiments;
- }
-
public LocalModel getFunction() {
return localModel;
}
- private Percept getPerceptsWithLesserImpactOnVolumeNotIncludedIn(ArrayList<Percept> containingRanges, Context c) {
- Percept p = null;
- double volumeLost = Double.MAX_VALUE;
- double vol;
-
- for (Percept percept : containingRanges) {
- if (!ranges.get(percept).isPerceptEnum()) {
- Range r = c.getRanges().get(percept);
- if (!(r.getStart() <= ranges.get(percept).getStart() && r.getEnd() >= ranges.get(percept).getEnd())) {
- if (ranges.get(percept).getNearestLimit(percept.getValue()) == false) {
- vol = ranges.get(percept).getEnd()
- - ranges.get(percept).simulateNegativeAVTFeedbackMin(percept.getValue());
- } else {
- vol = ranges.get(percept).simulateNegativeAVTFeedbackMax(percept.getValue())
- - ranges.get(percept).getStart();
- }
-
- for (Percept p2 : ranges.keySet()) {
- if (!ranges.get(p2).isPerceptEnum() && p2 != percept) {
- vol *= ranges.get(p2).getLenght();
- }
- }
- if (vol < volumeLost) {
- volumeLost = vol;
- p = percept;
- }
- }
- }
- }
- return p;
- }
-
- private Percept getPerceptsWithLesserImpactOnVolume(ArrayList<Percept> containingRanges) {
- Percept p = null;
- double volumeLost = Double.MAX_VALUE;
- double vol;
-
- for (Percept v : containingRanges) {
- if (!ranges.get(v).isPerceptEnum()) {
-
- if (ranges.get(v).getNearestLimit(v.getValue()) == false) {
- vol = ranges.get(v).getEnd() - ranges.get(v).simulateNegativeAVTFeedbackMin(v.getValue());
- } else {
- vol = ranges.get(v).simulateNegativeAVTFeedbackMax(v.getValue()) - ranges.get(v).getStart();
- }
-
- for (Percept v2 : ranges.keySet()) {
- if (!ranges.get(v).isPerceptEnum() && v2 != v) {
- vol *= ranges.get(v2).getLenght();
- }
- }
- if (vol < volumeLost) {
- volumeLost = vol;
- p = v;
- }
-
- }
-
- }
- return p;
- }
-
public double getRadiusByPercept(Percept pct) {
- return (this.getRangeByPerceptName(pct.getName()).getEnd()
- - this.getRangeByPerceptName(pct.getName()).getStart()) / 2;
+ Range rangeByPercept = this.getRangeByPercept(pct);
+ return (rangeByPercept.getEnd()
+ - rangeByPercept.getStart()) / 2;
}
public Range getRangeByPerceptName(String perceptName) {
@@ -386,12 +1538,122 @@ public class Context extends AmoebaAgent {
}
return null;
}
+
+ public Range getRangeByPercept(Percept pct) {
+ return ranges.get(pct);
+ }
public HashMap<Percept, Range> getRanges() {
return ranges;
}
-
+
public LocalModel getLocalModel() {
return localModel;
}
+
+ /**
+ * Called by the head when a context is selected as the best context
+ */
+ public void notifySelection() {
+ nSelection += 1;
+ }
+
+ /**
+ * Set the local model. Used mostly during save loading
+ * @param localModel
+ */
+ public void setLocalModel(LocalModel localModel) {
+ this.localModel = localModel;
+ this.localModel.setContext(this);
+ }
+
+
+ public void addWaitingRequest(EndogenousRequest request) {
+ waitingRequests.add(request);
+ getEnvironment().trace(TRACE_LEVEL.EVENT, new ArrayList<String>(Arrays.asList("ADDED WAITING REQUEST", this.getName(), ""+waitingRequests.size(), ""+request)));
+ }
+
+ public void deleteWaitingRequest(EndogenousRequest request) {
+ waitingRequests.remove(request);
+ }
+
+ public double getDistanceToRegressionAllowed() {
+ return regressionPerformance.getPerformanceIndicator();
+ }
+
+
+
+
+ /**
+ * Compute the color of a {@link Context} based on the coefficients of its {@link LocalModel}
+ * @param coefs
+ * @return
+ */
+ public String getColorForUnity() {
+
+ Double[] coefs = localModel.getCoef();
+
+ double upperBound = 255;
+ double dispersion = 100;
+
+
+ Double r = 0.0;
+ Double g = 0.0;
+ Double b = 0.0;
+
+
+
+
+ if(coefs.length>=3) {
+ r = normalizePositiveValues(upperBound, dispersion, Math.abs(coefs[0]));
+ g = normalizePositiveValues(upperBound, dispersion, Math.abs(coefs[1]));
+ b = normalizePositiveValues(upperBound, dispersion, Math.abs(coefs[2]));
+
+ if(r.isNaN() || g.isNaN() || b.isNaN()) {
+ r = 255.0;
+ g = 0.0;
+ b = 0.0;
+ }
+ }else if(coefs.length==2) {
+ r = normalizePositiveValues(upperBound, dispersion, Math.abs(coefs[0]));
+ g = normalizePositiveValues(upperBound, dispersion, Math.abs(coefs[1]));
+
+ if(r.isNaN() || g.isNaN() || b.isNaN()) {
+ r = 255.0;
+ g = 0.0;
+ }
+ }else if(coefs.length==1) {
+ r = normalizePositiveValues(upperBound, dispersion, Math.abs(coefs[0]));
+
+ if(r.isNaN() || g.isNaN() || b.isNaN()) {
+ r = 255.0;
+ }
+ }else {
+ r = 0.0;
+ g = 255.0;
+ b = 0.0;
+ }
+
+
+ Double[] ret = new Double[3];
+ ret[0] = r / 255.0d;
+ ret[1] = g / 255.0d;
+ ret[2] = b / 255.0d;
+
+ return ret[0] + "," + ret[1] + "," + ret[2] + ",200";
+ }
+
+ public static double normalizePositiveValues(double upperBound, double dispersion, double value) {
+ return upperBound * 2 * (-0.5 + 1 / (1 + Math.exp(-value / dispersion)));
+ }
+
+ public boolean isFlat() {
+ for(Percept pct:getAmas().getPercepts()) {
+ if(ranges.get(pct).getLenght()<0.00001) {
+ return true;
+ }
+ }
+ return false;
+ }
+
}
diff --git a/AMOEBAonAMAK/src/agents/context/CustomComparator.java b/AMOEBAonAMAK/src/agents/context/CustomComparator.java
new file mode 100644
index 0000000000000000000000000000000000000000..d7527addb52c430d9e0b8d050e35d5e17243331e
--- /dev/null
+++ b/AMOEBAonAMAK/src/agents/context/CustomComparator.java
@@ -0,0 +1,28 @@
+package agents.context;
+
+import java.io.Serializable;
+import java.util.Comparator;
+
+import agents.percept.Percept;
+
+public class CustomComparator implements Comparator<Context>, Serializable {
+
+
+ private Percept percept;
+ private String range;
+
+
+ public CustomComparator(Percept percept, String range){
+ this.percept = percept;
+ this.range = range;
+ }
+
+ @Override
+ public int compare(Context c1, Context c2) {
+
+ Double r1 = new Double(c1.getRanges().get(percept).getRange(range));
+ Double r2 = new Double(c2.getRanges().get(percept).getRange(range));
+
+ return r1.compareTo(r2);
+ }
+}
\ No newline at end of file
diff --git a/AMOEBAonAMAK/src/agents/context/Experiment.java b/AMOEBAonAMAK/src/agents/context/Experiment.java
index edaf73c8dd6a6cca2c60847fc56f81491dfe4339..3dcd44062b082e8f361f07c992f74fdea38407ca 100644
--- a/AMOEBAonAMAK/src/agents/context/Experiment.java
+++ b/AMOEBAonAMAK/src/agents/context/Experiment.java
@@ -1,29 +1,60 @@
package agents.context;
+import java.io.Serializable;
+import java.util.HashMap;
import java.util.LinkedHashMap;
+import agents.context.Context;
import agents.percept.Percept;
/**
* The Class Experiment.
*/
-public class Experiment {
+public class Experiment implements Serializable {
/** The values. */
private LinkedHashMap<Percept, Double> values = new LinkedHashMap<Percept, Double>();
-
+
/** The proposition. */
- private double proposition;
+ private double oracleProposition;
+
+ private Context context;
+
+ /**
+ * Instantiates a new experiment.
+ */
+ public Experiment(Context ctxt) {
+ context = ctxt;
+ }
+
+ /**
+ * Gets the ranges.
+ *
+ * @return the ranges
+ */
+ public HashMap<Percept, Double> getValuesAsHashMap() {
+ return values;
+ }
+ /**
+ * Sets the values.
+ *
+ * @param ranges the ranges
+ */
+ public void setValues(LinkedHashMap<Percept, Double> ranges) {
+ this.values = ranges;
+ }
+
/**
* Gets the values.
*
* @return the values
*/
- public LinkedHashMap<Percept, Double> getValues() {
+ public LinkedHashMap<Percept, Double> getValuesAsLinkedHashMap() {
return values;
}
+
/**
* Adds the dimension.
*
@@ -34,37 +65,55 @@ public class Experiment {
values.put(p, d);
}
+
/**
* Gets the proposition.
*
* @return the proposition
*/
- public double getProposition() {
- return proposition;
+ public double getOracleProposition() {
+ return oracleProposition;
}
+
/**
* Sets the proposition.
*
* @param proposition the new proposition
*/
- public void setProposition(double proposition) {
- this.proposition = proposition;
+ public void setOracleProposition(double oracleProposition) {
+ this.oracleProposition = oracleProposition;
}
-
+
/**
* Gets the values as array.
*
* @return the values as array
*/
public double[] getValuesAsArray() {
- double[] tab = new double[values.size()];
+ double [] tab = new double[values.size()];
int i = 0;
for (Percept p : values.keySet()) {
tab[i] = values.get(p);
i++;
}
-
+
return tab;
}
+
+
+ public String toString() {
+ String string = "\n";
+ for(Percept pct : values.keySet()) {
+ string += pct.getName() + " " + values.get(pct) + "\n";
+ }
+ string += "Oracle : " + oracleProposition + "\n";
+ return string;
+ }
+
+ @Override
+ public boolean equals(Object obj) {
+ // if it look like a duck, and quack like a duck, it's a duck
+ return getClass().equals(obj.getClass()) && toString().equals(obj.toString());
+ }
}
diff --git a/AMOEBAonAMAK/src/agents/context/Range.java b/AMOEBAonAMAK/src/agents/context/Range.java
index c311015f0ffd3d14e1f1d42f61dcaf4da509bdb9..5529a9ac87ad02a18553d7e6df475900d45f6517 100644
--- a/AMOEBAonAMAK/src/agents/context/Range.java
+++ b/AMOEBAonAMAK/src/agents/context/Range.java
@@ -1,486 +1,1640 @@
-package agents.context;
-
-import java.io.Serializable;
-
-import agents.percept.Percept;
-
-/**
- * The Class Range.
- */
-public class Range implements Comparable<Object>, Cloneable, Serializable {
- private static final long serialVersionUID = 1L;
-
- /** The start. */
- private double start;
-
- /** The end. */
- private double end;
-
- /** The start inclu. */
- private boolean start_inclu;
-
- /** The end inclu. */
- private boolean end_inclu;
-
- /** The context. */
- private Context context;
-
- /** The percept. */
- private Percept percept;
-
- /** The maxid. */
- private static int maxid = 0; // Used for debug purposes
-
- /** The id. */
- private int id;
-
- /** The Constant mininimalRange. */
- private static final double mininimalRange = 10;
-
- /** The Constant useAVT. */
- private static final boolean useAVT = true;
-
- /** The AV T delta min. */
- /*---------------AVT---------------*/
- private double AVT_deltaMin = 0.5;
-
- /** The AV T delta max. */
- private double AVT_deltaMax = 0.5;
-
- /** The AV T last feedback min. */
- private int AVT_lastFeedbackMin = 1;
-
- /** The AV T last feedback max. */
- private int AVT_lastFeedbackMax = 1;
-
- /** The AV T acceleration. */
- private double AVT_acceleration;
-
- /** The AV T deceleration. */
- private double AVT_deceleration;
-
- /** The AV T start ratio. */
- private double AVT_startRatio;
- /*---------------------------------*/
-
- /*------------Percent--------------*/
- /** The percent up. */
- // Only used if useAVT == false
- private static double percent_up = 0.2;
-
- /** The percent down. */
- private static double percent_down = 0.1;
- /*---------------------------------*/
-
- /**
- * Instantiates a new range.
- *
- * @param context the context
- * @param start the start
- * @param end the end
- * @param extendedrangeatcreation the extendedrangeatcreation
- * @param start_inclu the start inclu
- * @param end_inclu the end inclu
- * @param p the p
- */
- public Range(Context context, double start, double end, double extendedrangeatcreation, boolean start_inclu,
- boolean end_inclu, Percept p) {
- super();
-
- AVT_deceleration = context.getAmas().getEnvironment().getAVT_deceleration();
- AVT_acceleration = context.getAmas().getEnvironment().getAVT_acceleration();
- AVT_startRatio = context.getAmas().getEnvironment().getAVT_percentAtStart();
-
- this.percept = p;
- if (isPerceptEnum()) {
- this.setStart_inclu(start_inclu);
- this.setEnd_inclu(end_inclu);
- this.setStart(Math.round(p.getValue()));
- this.setEnd(Math.round(p.getValue()));
- } else {
- this.setStart_inclu(start_inclu);
- this.setEnd_inclu(end_inclu);
- this.setStart(start - Math.abs(extendedrangeatcreation * start));
- this.setEnd(end + Math.abs(extendedrangeatcreation * end));
- }
- this.context = context;
- id = maxid;
- maxid++;
-
- /* Initialization of AVT : a better way to do that should be developped */
- this.AVT_deltaMin = (end - start) * AVT_startRatio + 0.0001;
- this.AVT_deltaMax = (end - start) * AVT_startRatio + 0.0001;
- }
-
- /**
- * Method called by the context agent. Allow the range to adapt itself.
- *
- * @param c : the associated Context.
- * @param oracleValue the oracle value
- * @param p the p
- */
- public void adapt(Context c, double oracleValue, Percept p) {
- if (!isPerceptEnum()) {
- if (Range.useAVT) {
- adaptUsingAVT(c, oracleValue);
- } else {
- adaptWithoutAVT(c, oracleValue);
- }
- }
- }
-
- /**
- * Adapt without AVT.
- *
- * @param c the c
- * @param oracleValue the oracle value
- */
- private void adaptWithoutAVT(Context c, double oracleValue) {
- if (Math.abs(end - oracleValue) < Math.abs(oracleValue - start)) {
- adaptMaxWithoutAVT(c, oracleValue);
- } else {
- adaptMinWithoutAVT(c, oracleValue);
- }
- }
-
- /**
- * Adapt max without AVT.
- *
- * @param c the c
- * @param oracleValue the oracle value
- */
- private void adaptMaxWithoutAVT(Context c, double oracleValue) {
- if (contains(oracleValue) == 0.0) {
- this.setEnd(end - ((end - start) * percent_down));
- } else {
- this.setEnd(end + ((end - start) * percent_up));
- }
- }
-
- /**
- * Adapt min without AVT.
- *
- * @param c the c
- * @param oracleValue the oracle value
- */
- private void adaptMinWithoutAVT(Context c, double oracleValue) {
- if (contains(oracleValue) == 0.0) {
-
- this.setStart(start + ((end - start) * percent_up));
- } else {
- this.setStart(start - ((end - start) * percent_down));
- }
- }
-
- /**
- * Adapt using AVT.
- *
- * @param c the c
- * @param oracleValue the oracle value
- */
- private void adaptUsingAVT(Context c, double oracleValue) {
- if (Math.abs(end - oracleValue) < Math.abs(oracleValue - start)) {
- adaptMaxUsingAVT(c, oracleValue);
- } else {
- adaptMinUsingAVT(c, oracleValue);
- }
- }
-
- /**
- * Adapt max using AVT.
- *
- * @param c the c
- * @param oracleValue the oracle value
- */
- private void adaptMaxUsingAVT(Context c, double oracleValue) {
- // If value is contained, it's a negative feedback for AVT (ie : we must exclude
- // the value)
- if (contains(oracleValue) == 0.0) {
-
- if (AVT_lastFeedbackMax == 1) {
- AVT_deltaMax *= AVT_deceleration;
- } else {
- AVT_deltaMax *= AVT_acceleration;
- }
- this.setEnd(end - AVT_deltaMax);
-
- AVT_lastFeedbackMax = -1;
-
- } else {
-
- if (AVT_lastFeedbackMax == 1) {
- AVT_deltaMax *= AVT_acceleration;
- } else {
- AVT_deltaMax *= AVT_deceleration;
- }
- this.setEnd(end + AVT_deltaMax);
-
- AVT_lastFeedbackMax = 1;
- }
-
- }
-
- /**
- * Adapt min using AVT.
- *
- * @param c the c
- * @param oracleValue the oracle value
- */
- private void adaptMinUsingAVT(Context c, double oracleValue) {
- // If value is contained, it's a negative feedback for AVT (ie : we must exclude
- // the value)
- if (contains(oracleValue) == 0.0) {
-
- if (AVT_lastFeedbackMin == 1) {
- AVT_deltaMin *= AVT_deceleration;
- } else {
- AVT_deltaMin *= AVT_acceleration;
- }
- this.setStart(start + AVT_deltaMin);
-
- AVT_lastFeedbackMin = -1;
-
- } else {
-
- if (AVT_lastFeedbackMin == 1) {
- AVT_deltaMin *= AVT_acceleration;
- } else {
- AVT_deltaMin *= AVT_deceleration;
- }
- this.setStart(start - AVT_deltaMin);
-
- AVT_lastFeedbackMin = 1;
- }
-
- }
-
- /**
- * Simulate negative AVT feedback min.
- *
- * @param oracleValue the oracle value
- * @return the double
- */
- public double simulateNegativeAVTFeedbackMin(double oracleValue) {
-
- if (AVT_lastFeedbackMin == 1) {
- return start + (AVT_deltaMin * AVT_deceleration);
- } else {
- return start + (AVT_deltaMin * AVT_acceleration);
- }
-
- }
-
- /**
- * Simulate negative AVT feedback max.
- *
- * @param oracleValue the oracle value
- * @return the double
- */
- public double simulateNegativeAVTFeedbackMax(double oracleValue) {
-
- if (AVT_lastFeedbackMax == 1) {
- return end - (AVT_deltaMax * AVT_deceleration);
- } else {
- return end - (AVT_deltaMax * AVT_acceleration);
- }
-
- }
-
- /**
- * Check if the ranges is too small according to strategy.
- *
- * @return boolean representing if the range is too small.
- */
- public boolean isTooSmall() {
-
- return (end - start) < mininimalRange && !this.isPerceptEnum();
- }
-
- /*
- * (non-Javadoc)
- *
- * @see java.lang.Object#toString()
- */
- public String toString() {
- return ((start_inclu ? "[" : "]") + start + "," + end + (!end_inclu ? "[" : "]") + " Current value : "
- + percept.getValue() + " AVT_MIN : " + AVT_deltaMin + " AVT_MAX : " + AVT_deltaMax);
- }
-
- /**
- * Gets the context.
- *
- * @return the context
- */
- public Context getContext() {
- return context;
- }
-
- /**
- * Gets the AV twill to reduce.
- *
- * @param max the max
- * @return the AV twill to reduce
- */
- public double getAVTwillToReduce(boolean max) {
- if (max) {
- return this.AVT_lastFeedbackMax * this.AVT_deltaMax;
- } else {
- return this.AVT_lastFeedbackMin * this.AVT_deltaMin;
- }
- }
-
- /**
- * Match border with.
- *
- * @param c the c
- */
- public void matchBorderWith(Context c) {
- Range r = c.getRanges().get(percept);
- if (r.getStart() <= this.start && r.getEnd() >= this.end) {
- this.context.destroy();
- } else {
- if (Math.abs(r.getStart() - this.getEnd()) > Math.abs(r.getEnd() - this.getStart())) {
- // Change min
- this.setStart(r.getEnd());
- this.setStart_inclu(!r.isEnd_inclu());
-
- } else {
- // Change max
- this.setEnd(r.getStart());
- this.setEnd_inclu(!r.isStart_inclu());
- }
- }
-
- }
-
- /**
- * Contains.
- *
- * @param d : the value to test
- * @return -1 if lower, +1 if higher, 0 if contained
- */
- public int contains(Double d) {
- if ((d > start || (d >= start && start_inclu)) && (d < end || (d <= end && end_inclu))) {
- return 0;
- } else if (d <= start) {
- return -1;
- } else {
- return 1;
- }
- }
-
- /**
- * Checks if is end inclu.
- *
- * @return true, if is end inclu
- */
- public boolean isEnd_inclu() {
- return end_inclu;
- }
-
- /**
- * Sets the end inclu.
- *
- * @param end_inclu the new end inclu
- */
- public void setEnd_inclu(boolean end_inclu) {
- this.end_inclu = end_inclu;
- }
-
- /**
- * Checks if is start inclu.
- *
- * @return true, if is start inclu
- */
- public boolean isStart_inclu() {
- return start_inclu;
- }
-
- /**
- * Sets the start inclu.
- *
- * @param start_inclu the new start inclu
- */
- public void setStart_inclu(boolean start_inclu) {
- this.start_inclu = start_inclu;
- }
-
- /**
- * Gets the lenght.
- *
- * @return length of the range.
- */
- public double getLenght() {
- return end - start;
- }
-
- /**
- * Gets the nearest limit.
- *
- * @param d the d
- * @return max is true, min is false
- */
- public boolean getNearestLimit(double d) {
- return (d - start < end - d) ? false : true;
- }
-
- /**
- * Gets the start.
- *
- * @return the start
- */
- public double getStart() {
- return start;
- }
-
- /**
- * Gets the end.
- *
- * @return the end
- */
- public double getEnd() {
- return end;
- }
-
- /**
- * Checks if is percept enum.
- *
- * @return true, if is percept enum
- */
- public boolean isPerceptEnum() {
- return percept.isEnum();
- }
-
- /*
- * (non-Javadoc)
- *
- * @see java.lang.Comparable#compareTo(java.lang.Object)
- */
- @Override
- public int compareTo(Object o) {
- return this.compareTo(o);
- }
-
- private void setStart(double newStartValue) {
- this.start = newStartValue;
- if (this.context != null) {
- this.percept.updateContextProjectionStart(this.context);
- }
-
- }
-
- private void setEnd(double newEndValue) {
- this.end = newEndValue;
- if (this.context != null) {
- this.percept.updateContextProjectionEnd(this.context);
- }
- }
-
- public Range clone() throws CloneNotSupportedException {
- return (Range) super.clone();
- }
-
- public int getId() {
- return id;
- }
-}
+package agents.context;
+
+import java.io.Serializable;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.HashMap;
+
+import agents.percept.Percept;
+import kernel.World;
+import ncs.NCS;
+import utils.Pair;
+import utils.TRACE_LEVEL;
+
+/**
+ * The Class Range.
+ */
+public class Range implements Serializable, Comparable, Cloneable {
+
+ private double start = 0;
+ private double end = 0;
+
+ private boolean start_inclu;
+ private boolean end_inclu;
+
+ private double value;
+ private double oldValue;
+
+ private double alphaFactor;
+
+ private int lastStartTickModification = 0;
+ private int lastEndTickModification = 0;
+
+ private int lastStartDirection = 0;
+ private int lastEndDirection = 0;
+
+ private int startCriticality = 0;
+ private int endCriticality = 0;
+
+ private double startIncrement;
+ private double endIncrement;
+
+ /** The Constant startLenghtRatio. */
+ /*
+ * The weight in an interpolation : the impact on action for a +1 change in this
+ * range value
+ */
+ private final static double minLenghtRatio = 0;
+
+ private World world;
+ private Context context;
+ private Percept percept;
+
+ public static int maxid = 0; // TODO for debug purposes
+ public int id;
+ public static final double mininimalRange = 1;
+ private static final boolean useAVT = true;
+
+ /*---------------AVT---------------*/
+ private double AVT_deltaStart = 0.5;
+ private double AVT_deltaEnd = 0.5;
+
+ private int AVT_lastFeedbackStart = 1;
+ private int AVT_lastFeedbackEnd = 1;
+
+ private double AVT_acceleration;
+ private double AVT_deceleration;
+
+ private double AVT_minRatio;
+ /*---------------------------------*/
+
+ /*------------Percent--------------*/
+ // Only used if useAVT == false
+ static public double percent_up = 0.2;
+ static public double percent_down = 0.1;
+ /*---------------------------------*/
+
+ public double increment_up = 0.05;
+ public double increment_down = 0.05;
+
+ /**
+ * Instantiates a new range.
+ *
+ * @param context the context
+ * @param start the start
+ * @param end the end
+ * @param extendedrangeatcreation the extendedrangeatcreation
+ * @param start_inclu the start inclu
+ * @param end_inclu the end inclu
+ * @param p the p
+ */
+ public Range(Context context, double start, double end, double extendedrangeatcreation, boolean start_inclu,
+ boolean end_inclu, Percept p) {
+ super();
+
+ world = context.getAmas().getEnvironment();
+
+ AVT_deceleration = world.getAVT_deceleration();
+ AVT_acceleration = world.getAVT_acceleration();
+ AVT_minRatio = world.getAVT_percentAtStart();
+
+ this.percept = p;
+ if (isPerceptEnum()) {
+ this.setStart_inclu(start_inclu);
+ this.setEnd_inclu(end_inclu);
+ this.setStart(Math.round(p.getValue()));
+ this.setEnd(Math.round(p.getValue()));
+ } else {
+ this.setStart_inclu(start_inclu);
+ this.setEnd_inclu(end_inclu);
+ this.setStart(start - Math.abs(extendedrangeatcreation * start));
+ this.setEnd(end + Math.abs(extendedrangeatcreation * end));
+ }
+ this.context = context;
+ id = maxid;
+ maxid++;
+
+ /* Initialization of AVT : a better way to do that should be developped */
+// this.AVT_deltaStart = (end - start) * AVT_minRatio + 0.0001;
+// this.AVT_deltaEnd = (end - start) * AVT_minRatio + 0.0001;
+ this.AVT_deltaStart = getLenght() * 0.2 + 0.0001;
+ this.AVT_deltaEnd = getLenght() * 0.2 + 0.0001;
+ ////// System.out.println(world.getScheduler().getTick() + "\t" +
+ ////// context.getName() + "\t" + percept.getName()+ "\t" + "Creation" + "\t" +
+ ////// "START" + "\t" + AVT_deltaStart);
+ ////// System.out.println(world.getScheduler().getTick() + "\t" +
+ ////// context.getName() + "\t" + percept.getName()+ "\t" + "Creation" + "\t" +
+ ////// "END" + "\t" + AVT_deltaEnd);
+
+ startIncrement = 0.25 * world.getMappingErrorAllowed() * percept.getMinMaxDistance();
+ endIncrement = startIncrement;
+ }
+
+ /**
+ * Extends the range to the specified target value.
+ *
+ * @param target : value to be included
+ * @param p the p
+ * @return true if the context was extended, false else.
+ */
+ public boolean extend(double target, Percept p) {
+ int c = contains(target);
+ if (c == -1) {
+// AVT_deltaStart = Math.abs(target-getStart());
+// AVT_lastFeedbackStart = 1;
+ this.setStart(target);
+ return true;
+ } else if (c == 1) {
+// AVT_deltaEnd = Math.abs(target-getEnd());
+// AVT_lastFeedbackStart = 1;
+ this.setEnd(target);
+ return true;
+ } else {
+ return false;
+ }
+
+ }
+
+ public void shrink(double target, Percept p) {
+
+ if (Math.abs(getStart() - target) < Math.abs(getEnd() - target)) {
+ this.setStart(target + this.getRadius() * 0.02);
+ } else {
+ this.setEnd(target - this.getRadius() * 0.02);
+ }
+ }
+
+ /**
+ * Method called by the context agent. Allow the range to adapt itself.
+ *
+ * @param c : the associated Context.
+ * @param oracleValue the oracle value
+ * @param p the p
+ */
+ public void adapt(Double oracleValue, double increment) {
+ if (!isPerceptEnum()) {
+
+ double minIncrement = Math.min(increment, getIncrement());
+
+ staticAdapt(oracleValue, minIncrement);
+
+ // adaptUsingAVT(c, oracleValue);
+ // adaptWithoutAVT(c, oracleValue);
+
+// if (Range.useAVT) {
+// adaptUsingAVT(c, oracleValue);
+// } else {
+// adaptWithoutAVT(c, oracleValue);
+// }
+ }
+ }
+
+ public void adapt(Double oracleValue) {
+ if (!isPerceptEnum()) {
+
+ staticAdapt(oracleValue, getIncrement());
+
+ // adaptUsingAVT(c, oracleValue);
+ // adaptWithoutAVT(c, oracleValue);
+
+// if (Range.useAVT) {
+// adaptUsingAVT(c, oracleValue);
+// } else {
+// adaptWithoutAVT(c, oracleValue);
+// }
+ }
+ }
+
+ /**
+ * Adapt without AVT.
+ *
+ * @param c the c
+ * @param oracleValue the oracle value
+ */
+ private void adaptWithoutAVT(Context c, double oracleValue) {
+ if (Math.abs(end - oracleValue) < Math.abs(oracleValue - start)) {
+ adaptEndWithoutAVT(c, oracleValue);
+ } else {
+ adaptStartWithoutAVT(c, oracleValue);
+ }
+ }
+
+ /**
+ * Adapt End without AVT.
+ *
+ * @param c the c
+ * @param oracleValue the oracle value
+ */
+ private void adaptEndWithoutAVT(Context c, double oracleValue) {
+ if (contains(oracleValue) == 0.0) {
+ this.setEnd(end - ((end - start) * percent_down));
+ } else {
+ this.setEnd(end + ((end - start) * percent_up));
+ }
+ }
+
+ /**
+ * Adapt start without AVT.
+ *
+ * @param c the c
+ * @param oracleValue the oracle value
+ */
+ private void adaptStartWithoutAVT(Context c, double oracleValue) {
+ if (contains(oracleValue) == 0.0) {
+
+ this.setStart(start + ((end - start) * percent_up));
+ } else {
+ this.setStart(start - ((end - start) * percent_down));
+ }
+ }
+
+ /**
+ * Adapt using AVT.
+ *
+ * @param c the c
+ * @param oracleValue the oracle value
+ */
+ private void adaptUsingAVT(Context c, Double oracleValue) {
+
+ if (Math.abs(end - oracleValue) < Math.abs(oracleValue - start)) {
+ adaptEndUsingAVT(oracleValue);
+ } else {
+ adaptStartUsingAVT(oracleValue);
+ }
+
+ }
+
+ private void staticAdapt(double oracleValue, double increment) {
+ if (Math.abs(end - oracleValue) < Math.abs(oracleValue - start)) {
+ adaptEnd(oracleValue, increment);
+ } else {
+ adaptStart(oracleValue, increment);
+ }
+ }
+
+ /**
+ * Adapt End using AVT.
+ *
+ * @param c the c
+ * @param oracleValue the oracle value
+ */
+ private void adaptEndUsingAVT(double oracleValue) {
+
+ //// System.out.print(world.getScheduler().getTick() + "\t" + context.getName()
+ //// + "\t" + percept.getName()+ "\t" + " AdaptEndUsingAVT");
+
+ if (contains(oracleValue) == 0.0) { // If value is contained, it's a negative feedback for AVT (ie : we must
+ // exclude the value)
+
+ //// System.out.print( "\tContained : True" );
+
+ if (AVT_lastFeedbackEnd == 1) {
+ AVT_deltaEnd *= AVT_deceleration;
+ //// System.out.print(" AVT_deceleration AVT_deltaEnd : " + "\t" +
+ //// AVT_deltaEnd);
+ } else {
+ AVT_deltaEnd *= AVT_acceleration;
+ //// System.out.print(" AVT_acceleration AVT_deltaEnd : " + "\t" +
+ //// AVT_deltaEnd);
+ }
+ this.setEnd(end - AVT_deltaEnd);
+
+ //// System.out.print("\tAVT_lastFeedbackEn\t" + AVT_lastFeedbackEnd);
+ AVT_lastFeedbackEnd = -1;
+ //// System.out.print("\t" + AVT_lastFeedbackEnd + "\n");
+
+ } else {
+ //// System.out.print( "\tContained : False" );
+ if (AVT_lastFeedbackEnd == 1) {
+ AVT_deltaEnd *= AVT_acceleration;
+ //// System.out.print(" AVT_acceleration AVT_deltaEnd : " + "\t" +
+ //// AVT_deltaEnd);
+ } else {
+ AVT_deltaEnd *= AVT_deceleration;
+ //// System.out.print(" AVT_deceleration AVT_deltaEnd : " + "\t" +
+ //// AVT_deltaEnd);
+ }
+ this.setEnd(end + AVT_deltaEnd);
+
+ //// System.out.print("\tAVT_lastFeedbackEn\t" + AVT_lastFeedbackEnd);
+ AVT_lastFeedbackEnd = 1;
+ //// System.out.print("\t" + AVT_lastFeedbackEnd + "\n");
+ }
+
+ }
+
+ public void endogenousAdaptEndUsingAVT() {
+
+ //// System.out.print(world.getScheduler().getTick() + "\t" + context.getName()
+ //// + "\t" + percept.getName()+ "\t" + " AdaptEndUsingAVT");
+
+ AVT_deltaEnd *= AVT_deceleration;
+ //// System.out.print(" AVT_deceleration AVT_deltaEnd : " + "\t" +
+ //// AVT_deltaEnd);
+
+ //// System.out.print("\tAVT_lastFeedbackEn\t" + AVT_lastFeedbackEnd);
+ AVT_lastFeedbackEnd = 0;
+ //// System.out.print("\t" + AVT_lastFeedbackEnd + "\n");
+
+ }
+
+ public void endogenousAdaptStartUsingAVT() {
+
+ //// System.out.print(world.getScheduler().getTick() + "\t" + context.getName()
+ //// + "\t" + percept.getName()+ "\t" + " AdaptEndUsingAVT");
+
+ AVT_deltaStart *= AVT_deceleration;
+ //// System.out.print(" AVT_deceleration AVT_deltaStart : " + "\t" +
+ //// AVT_deltaStart);
+
+ //// System.out.print("\tAVT_lastFeedbackStart\t" + AVT_lastFeedbackStart);
+ AVT_lastFeedbackStart = 0;
+ //// System.out.print("\t" + AVT_lastFeedbackStart + "\n");
+
+ }
+
+ private void adaptEnd(double oracleValue, double increment) {
+ world.trace(TRACE_LEVEL.STATE, new ArrayList<String>(Arrays.asList("INCREMENT ON END ADAPT", context.getName(), percept.getName(), "" + increment )));
+
+ classicEndAdapt(oracleValue, increment);
+ // adaptEndWithSplitting(oracleValue, increment);
+
+ }
+
+ private void classicEndAdapt(double oracleValue, double increment) {
+ if (!(contains(oracleValue) == 0.0)) { // value not contained --> end range will grow (growing direction = 1)
+
+ if (lastEndDirection == -1) { // opposite direction -> negative feedback
+ endCriticality = 1;
+ } else if (lastEndDirection == 1) { // same direction -> positive feedback
+ endCriticality = 0;
+ }
+ lastEndDirection = 1; // growing direction
+
+ if (endCriticality == 1) { // negative feedback -> increment decreases
+ endIncrement /= 3;
+ } else if (endCriticality == 0) { // positive feedback -> increment increases
+ endIncrement = Math.min(percept.getRadiusContextForCreation(), endIncrement * 2);
+ // endIncrement *=2;
+ }
+
+ this.setEnd(end + endIncrement);
+ } else { // value contained --> end range will shrink (shrinking direction = -1)
+
+ if (lastEndDirection == 1) { // opposite direction -> negative feedback
+ endCriticality = 1;
+ } else if (lastEndDirection == -1) { // same direction -> positive feedback
+ endCriticality = 0;
+ }
+ lastEndDirection = -1; // shrinking direction
+
+ if (endCriticality == 1) { // negative feedback -> increment decreases
+ endIncrement /= 2;
+ } else if (endCriticality == 0) { // positive feedback -> increment increases
+ endIncrement = Math.min(percept.getRadiusContextForCreation(), endIncrement * 2);
+ // endIncrement *=2;
+ }
+
+ this.setEnd(end - endIncrement);
+
+ }
+
+ }
+
+ private void adaptEndWithSplitting(double oracleValue, double increment) {
+ world.trace(TRACE_LEVEL.STATE, new ArrayList<String>(Arrays.asList("" + increment, "INCREMENT")));
+
+ ArrayList<Context> bordererContexts = new ArrayList<Context>();
+
+ if (!(contains(oracleValue) == 0.0)) {
+
+ for (Context ctxt : context.getAmas().getHeadAgent().getActivatedNeighborsContexts()) {
+
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList(context.getName(), "" + this.distance(ctxt.getRanges().get(this.percept)),
+ "DISTANCE SPLIT", percept.getName(), ctxt.getName())));
+
+ if (Math.abs(this.distance(ctxt.getRanges().get(this.percept))) <= increment
+ && ctxt.getRanges().get(this.percept).getCenter() > this.getCenter()) {
+
+ boolean bordererContextTest = true;
+ for (Percept pct : context.getAmas().getPercepts()) {
+
+ if (pct != this.percept) {
+
+ Range contextRangeOnOtherPercept = this.context.getRanges().get(pct);
+ Range otherContextRangeOnOtherPercept = ctxt.getRanges().get(pct);
+
+ bordererContextTest = bordererContextTest
+ && (contextRangeOnOtherPercept.distance(otherContextRangeOnOtherPercept) < 0);
+
+ }
+ }
+
+ if (bordererContextTest) {
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList(context.getName(), "END BORDER CONTEXT",
+ percept.getName(), ctxt.getName())));
+ bordererContexts.add(ctxt);
+ }
+
+ }
+
+ }
+ if (bordererContexts.size() > 0) {
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("END BORDER CONTEXT", percept.getName())));
+ double minAlternativeIncrement = increment;
+ double alternativeIncrement;
+ for (Context ctxt : bordererContexts) {
+ alternativeIncrement = Math.abs(this.distance(ctxt.getRanges().get(this.percept)));
+ if (alternativeIncrement < minAlternativeIncrement) {
+ minAlternativeIncrement = alternativeIncrement;
+ }
+ }
+ this.setEnd(end + minAlternativeIncrement);
+ growWithBorderContext();
+ } else {
+ this.setEnd(end + increment);
+ }
+
+ // this.setEnd(end + increment);
+ // this.setEnd(end + getIncrementDependingOnNeighboorDistances("end"));
+ // this.setEnd(end + getMaxIncrement("end"));
+ } else {
+
+ this.setEnd(end - increment);
+ // this.setEnd(end - getIncrementDependingOnNeighboorDistances("end"));
+ }
+
+ }
+
+ private void growWithBorderContext() {
+// Context newContext = new Context(world, world.getScheduler().getHeadAgent(), this.context);
+// world.getScheduler().getHeadAgent().addActivatedContext(newContext);
+// world.getScheduler().getHeadAgent().addRequestNeighbor(newContext);
+ }
+
+ /**
+ * Adapt start using AVT.
+ *
+ * @param c the c
+ * @param oracleValue the oracle value
+ */
+ private void adaptStartUsingAVT(double oracleValue) {
+
+ //// System.out.print(world.getScheduler().getTick() + "\t" + context.getName()
+ //// + "\t" + percept.getName()+ "\t" + " AdaptStartUsingAVT");
+
+ if (contains(oracleValue) == 0.0) { // If value is contained, it's a negative feedback for AVT (ie : we must
+ // exclude the value)
+
+ //// System.out.print( "\tContained : True" );
+ if (AVT_lastFeedbackStart == 1) {
+ AVT_deltaStart *= AVT_deceleration;
+ //// System.out.print(" AVT_deceleration AVT_deltaStart : " + "\t" +
+ //// AVT_deltaStart);
+ } else {
+ AVT_deltaStart *= AVT_acceleration;
+ //// System.out.print(" AVT_acceleration AVT_deltaStart : " + "\t" +
+ //// AVT_deltaStart);
+ }
+ this.setStart(start + AVT_deltaStart);
+
+ //// System.out.print("\tAVT_lastFeedbackStart\t" + AVT_lastFeedbackStart);
+ AVT_lastFeedbackStart = -1;
+ //// System.out.print("\t" + AVT_lastFeedbackStart + "\n");
+
+ } else {
+
+ //// System.out.print( "\tContained : False" );
+ if (AVT_lastFeedbackStart == 1) {
+ AVT_deltaStart *= AVT_acceleration;
+ //// System.out.print(" AVT_acceleration AVT_deltaStart : " + "\t" +
+ //// AVT_deltaStart);
+ } else {
+ AVT_deltaStart *= AVT_deceleration;
+ //// System.out.print(" AVT_deceleration AVT_deltaStart : " + "\t" +
+ //// AVT_deltaStart);
+ }
+ this.setStart(start - AVT_deltaStart);
+
+ //// System.out.print("\tAVT_lastFeedbackStart\t" + AVT_lastFeedbackStart);
+ AVT_lastFeedbackStart = 1;
+ //// System.out.print("\t" + AVT_lastFeedbackStart + "\n");
+ }
+
+ }
+
+ private void adaptStart(double oracleValue, double increment) {
+ world.trace(TRACE_LEVEL.STATE, new ArrayList<String>(Arrays.asList("INCREMENT ON END ADAPT", context.getName(), percept.getName(), "" + increment )));
+
+
+ classicStartAdapt(oracleValue, increment);
+ // adaptStartWithSplitting(oracleValue, increment);
+
+ }
+
+ private void classicStartAdapt(double oracleValue, double increment) {
+ if (!(contains(oracleValue) == 0.0)) {
+
+ if (lastStartDirection == -1) {
+ startCriticality = 1;
+ } else if (lastStartDirection == 1) {
+ startCriticality = 0;
+ }
+ lastStartDirection = 1;
+
+ if (startCriticality == 1) {
+ startIncrement /= 3;
+ } else if (startCriticality == 0) {
+
+ startIncrement = Math.min(percept.getRadiusContextForCreation(), startIncrement * 2);
+ // startIncrement *=2;
+ }
+
+// System.out.println(world.getScheduler().getTick() + " " +
+// this.context.getName() + " " +
+// this.percept.getName()+ " " +
+// lastStartDirection + " " +
+// " ++ " +
+// startCriticality + " " +
+// startIncrement
+// );
+
+ this.setStart(start - startIncrement);
+
+ // this.setStart(start - getIncrementDependingOnNeighboorDistances("start"));
+ // this.setStart(start - getMaxIncrement("start"));
+
+ } else {
+ if (lastStartDirection == 1) {
+ startCriticality = 1;
+ } else if (lastStartDirection == -1) {
+ startCriticality = 0;
+ }
+ lastStartDirection = -1;
+
+ if (startCriticality == 1) {
+ startIncrement /= 2;
+ } else if (startCriticality == 0) {
+ startIncrement = Math.min(percept.getRadiusContextForCreation(), startIncrement * 2);
+ // startIncrement *=2;
+ }
+
+// System.out.println(world.getScheduler().getTick() + " " +
+// this.context.getName() + " " +
+// this.percept.getName()+ " " +
+// lastStartDirection + " " +
+// " -- " +
+// startCriticality + " " +
+// startIncrement
+// );
+
+ this.setStart(start + startIncrement);
+ }
+
+ // this.setStart(start + getIncrementDependingOnNeighboorDistances("start"));
+
+ // this.adaptStartUsingAVT(oracleValue);
+ }
+
+ private void adaptStartWithSplitting(double oracleValue, double increment) {
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("" + increment, "INCREMENT")));
+ ArrayList<Context> bordererContexts = new ArrayList<Context>();
+
+ if (!(contains(oracleValue) == 0.0)) {
+
+ for (Context ctxt : context.getAmas().getHeadAgent().getActivatedNeighborsContexts()) {
+
+ if (Math.abs(this.distance(ctxt.getRanges().get(this.percept))) <= increment
+ && ctxt.getRanges().get(this.percept).getCenter() < this.getCenter()) {
+
+ boolean bordererContextTest = true;
+ for (Percept pct : context.getAmas().getPercepts()) {
+
+ if (pct != this.percept) {
+
+ Range contextRangeOnOtherPercept = this.context.getRanges().get(pct);
+ Range otherContextRangeOnOtherPercept = ctxt.getRanges().get(pct);
+
+ bordererContextTest = bordererContextTest
+ && (contextRangeOnOtherPercept.distance(otherContextRangeOnOtherPercept) < 0);
+
+ }
+ }
+
+ if (bordererContextTest) {
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList("START BORDER CONTEXT", percept.getName(), ctxt.getName())));
+ bordererContexts.add(ctxt);
+ }
+
+ }
+
+ }
+ if (bordererContexts.size() > 0) {
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("START BORDER CONTEXT", percept.getName())));
+ double minAlternativeIncrement = increment;
+ double alternativeIncrement;
+ for (Context ctxt : bordererContexts) {
+ alternativeIncrement = Math.abs(this.distance(ctxt.getRanges().get(this.percept)));
+ if (alternativeIncrement < minAlternativeIncrement) {
+ minAlternativeIncrement = alternativeIncrement;
+ }
+ }
+ this.setStart(start - minAlternativeIncrement);
+ growWithBorderContext();
+ } else {
+ this.setStart(start - increment);
+ }
+
+ // this.setStart(start - getIncrementDependingOnNeighboorDistances("start"));
+ // this.setStart(start - getMaxIncrement("start"));
+
+ } else {
+ this.setStart(start + increment);
+ }
+
+ // this.setStart(start + getIncrementDependingOnNeighboorDistances("start"));
+
+ // this.adaptStartUsingAVT(oracleValue);
+ }
+
+ public double getIncrement() {
+ double increment = 0.25 * world.getMappingErrorAllowed() * percept.getMinMaxDistance();
+ // double increment = 10*world.getIncrements()*this.getRadius();
+ // world.trace(new
+ // ArrayList<String>(Arrays.asList(this.getContext().getName(),percept.getName(),
+ // "INCREMENT", ""+increment)));
+ return increment;
+ }
+
+ private double getIncrementDependingOnNeighboorDistances(String rangeSide) {
+ double increment = this.getRadius() / 2;
+ double incrementSum = 0.0;
+ ArrayList<Context> neighbors = new ArrayList<Context>();
+
+ for (Context ctxt : context.getAmas().getHeadAgent().getActivatedNeighborsContexts()) {
+
+ if (ctxt != this.context) {
+
+ if (rangeSide.equals("start")) {
+ double startDistance = startDistance(ctxt.getRanges().get(percept));
+ if (startDistance < this.getRadius() / 2) {
+ if (startDistance > incrementSum) {
+ incrementSum = startDistance;
+ }
+
+ }
+ } else if (rangeSide.equals("end")) {
+ double endDistance = endDistance(ctxt.getRanges().get(percept));
+ if (endDistance < this.getRadius() / 2) {
+ if (endDistance > incrementSum) {
+ incrementSum = endDistance;
+ }
+ }
+ }
+ }
+ }
+ if (incrementSum != 0.0) {
+ increment = incrementSum;
+ }
+
+ return increment;
+ }
+
+ private double getMaxIncrement(String rangeSide) {
+ double increment = world.getIncrements() * percept.getMinMaxDistance();
+ double possibleIncrement;
+
+ // System.out.println("INI INCREMENT " + increment);
+ // System.out.println("NEIGHBORS " +
+ // world.getScheduler().getHeadAgent().getActivatedNeighborsContexts().size());
+ for (Context ctxt : context.getAmas().getHeadAgent().getActivatedNeighborsContexts()) {
+
+ if (ctxt != this.context) {
+// possibleIncrement = this.distance(ctxt.getRanges().get(this.percept));
+// //System.out.println("POS INCREMENT " + possibleIncrement);
+// if(possibleIncrement<increment) {
+// increment = possibleIncrement;
+// }
+ if (rangeSide.equals("start")) {
+ if (this.getStart() > ctxt.getRanges().get(this.percept).getEnd()) {
+ possibleIncrement = this.distance(ctxt.getRanges().get(this.percept));
+ if (possibleIncrement < increment) {
+ increment = possibleIncrement;
+ }
+ }
+ } else if (rangeSide.equals("end")) {
+ if (this.getEnd() < ctxt.getRanges().get(this.percept).getStart()) {
+ possibleIncrement = this.distance(ctxt.getRanges().get(this.percept));
+ if (possibleIncrement < increment) {
+ increment = possibleIncrement;
+ }
+ }
+ }
+ }
+
+ }
+
+ // world.trace(new ArrayList<String>(Arrays.asList(this.context.getName(),
+ // this.percept.getName(), rangeSide +" INCREMENT ", ""+increment)));
+ return increment;
+ }
+
+ /**
+ * Simulate negative AVT feedback start.
+ *
+ * @param oracleValue the oracle value
+ * @return the double
+ */
+ public double simulateNegativeAVTFeedbackStart(double oracleValue) {
+
+ //// System.out.print(world.getScheduler().getTick() + "\t" + context.getName()
+ //// + "\t" + percept.getName()+ "\t" );
+ if (AVT_lastFeedbackStart == 1) {
+ ////// System.out.println("simulateNegativeAVTFeedbackStart :" +
+ ////// Math.abs(AVT_deltaStart * AVT_deceleration) + "\t" + "AVT_deltaStart : "
+ ////// + "\t" + AVT_deltaStart);
+ return start + (AVT_deltaStart * AVT_deceleration);
+ } else {
+ ////// System.out.println("simulateNegativeAVTFeedbackStart :" +
+ ////// Math.abs(AVT_deltaStart * AVT_acceleration) + "\t" + "AVT_deltaStart : "
+ ////// + "\t" + AVT_deltaStart);
+ return start + (AVT_deltaStart * AVT_acceleration);
+ }
+
+ }
+
+ /**
+ * Simulate negative AVT feedback End.
+ *
+ * @param oracleValue the oracle value
+ * @return the double
+ */
+ public double simulateNegativeAVTFeedbackEnd(double oracleValue) {
+
+ //// System.out.print(world.getScheduler().getTick() + "\t" + context.getName()
+ //// + "\t" + percept.getName()+ "\t" );
+ if (AVT_lastFeedbackEnd == 1) {
+ ////// System.out.println("simulateNegativeAVTFeedbackEnd :" +
+ ////// Math.abs(AVT_deltaEnd * AVT_deceleration) + "\t" + "AVT_deltaEnd : " +
+ ////// "\t" + AVT_deltaEnd);
+ return end - (AVT_deltaEnd * AVT_deceleration);
+ } else {
+ ////// System.out.println("simulateNegativeAVTFeedbackEnd :" +
+ ////// Math.abs(AVT_deltaEnd * AVT_acceleration) + "\t" + "AVT_deltaEnd : " +
+ ////// "\t" + AVT_deltaEnd);
+ return end - (AVT_deltaEnd * AVT_acceleration);
+ }
+
+ }
+
+ /**
+ * Check if the ranges is too small according to strategy.
+ *
+ * @return boolean representing if the range is too small.
+ */
+ public boolean isTooSmall() {
+
+ if((end - start) < percept.getMappingErrorAllowedMin()) {
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList(this.context.getName(), this.percept.getName(), "TOO SMALL DISTANCE", "" + (end - start))));
+ }
+
+ return ((end - start) < percept.getMappingErrorAllowedMin()) && !this.isPerceptEnum();
+ }
+
+ /**
+ * Gets the old value.
+ *
+ * @return the old value
+ */
+ public double getOldValue() {
+ return oldValue;
+ }
+
+ /**
+ * Sets the old value.
+ *
+ * @param oldValue the new old value
+ */
+ public void setOldValue(double oldValue) {
+ this.oldValue = oldValue;
+ }
+
+ /*
+ * (non-Javadoc)
+ *
+ * @see java.lang.Object#toString()
+ */
+ public String toString() {
+ return ((start_inclu ? "[" : "]") + start + "," + end
+ + (!end_inclu ? "[" : "]") + " Current value : " + percept.getValue()
+ + "\n lastStartDirection : " + lastStartDirection
+ + "\n lastEndDirection : " + lastEndDirection
+ + "\n startCriticality : " + startCriticality
+ + "\n endCriticality : " + endCriticality
+ + "\n startIncrement : " + startIncrement
+ + "\n endIncrement : " + endIncrement
+
+ );
+ }
+
+ /**
+ * Gets the context.
+ *
+ * @return the context
+ */
+ public Context getContext() {
+ return context;
+ }
+
+ /**
+ * Sets the context.
+ *
+ * @param context the new context
+ */
+ public void setContext(Context context) {
+ this.context = context;
+ }
+
+ /**
+ * Gets the AV twill to reduce.
+ *
+ * @param End the End
+ * @return the AV twill to reduce
+ */
+ public double getAVTwillToReduce(boolean End) {
+ if (End) {
+ return this.AVT_lastFeedbackEnd * this.AVT_deltaEnd;
+ } else {
+ return this.AVT_lastFeedbackStart * this.AVT_deltaStart;
+ }
+ }
+
+ /**
+ * Match border with.
+ *
+ * @param c the c
+ */
+ public void matchBorderWith(Context c) {
+ Range r = c.getRanges().get(percept);
+ if (r.getStart() <= this.start && r.getEnd() >= this.end) {
+ this.context.destroy();
+ } else {
+ if (Math.abs(r.getStart() - this.getEnd()) > Math.abs(r.getEnd() - this.getStart())) {
+ // Change start
+// AVT_deltaStart = Math.abs(r.getEnd()-getStart());
+// AVT_lastFeedbackStart = 1;
+ this.setStart(r.getEnd());
+ this.setStart_inclu(!r.isEnd_inclu());
+
+ } else {
+ // Change End
+// AVT_deltaEnd = Math.abs(r.getStart()-getEnd());
+// AVT_lastFeedbackEnd = 1;
+ this.setEnd(r.getStart());
+ this.setEnd_inclu(!r.isStart_inclu());
+ }
+ }
+
+ }
+
+ public void matchBorderWithBestContext(Context bestContext) {
+ ////// System.out.println("Match border " + percept.getName());
+
+ Range bestContextRanges = bestContext.getRanges().get(percept);
+
+ if (bestContextRanges.getStart() <= this.start && this.end <= bestContextRanges.getEnd()) {
+
+ ////// System.out.println(context.getName() + " DIES");
+ this.context.destroy();
+
+ } else {
+
+ if (Math.abs(bestContextRanges.getStart() - this.getEnd()) >= Math
+ .abs(bestContextRanges.getEnd() - this.getStart())) {
+
+ matchBorderOnOverlap(bestContextRanges, bestContextRanges.getEnd());
+ } else {
+ matchBorderOnOverlap(bestContextRanges, bestContextRanges.getStart());
+ }
+ }
+
+ }
+
+ public void adaptTowardsBorder(Context bestContext) {
+
+ Range bestContextRanges = bestContext.getRanges().get(percept);
+
+ if (bestContextRanges.getStart() <= this.start && this.end <= bestContextRanges.getEnd()) {
+
+ this.context.destroy();
+
+ } else {
+
+ if (Math.abs(bestContextRanges.getStart() - this.getEnd()) >= Math
+ .abs(bestContextRanges.getEnd() - this.getStart())) {
+
+ setOnConcurentOverlap(bestContextRanges, bestContextRanges.getEnd());
+ } else {
+ setOnConcurentOverlap(bestContextRanges, bestContextRanges.getStart());
+ }
+ }
+
+ }
+
+ public void adaptOnOverlap(Range overlappingContextRanges, double border) {
+
+ world.trace(TRACE_LEVEL.EVENT, new ArrayList<String>(Arrays.asList(this.context.getName(), percept.getName(),
+ "*********************************************************************************************************** ADAPT ON OVERLAP")));
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList(this.context.getName(), overlappingContextRanges.getContext().getName())));
+ double increment = Math.min(Math.abs(this.distance(overlappingContextRanges)), getIncrement());
+
+ HashMap<Percept, Pair<Double, Double>> newContextDimensions = new HashMap<Percept, Pair<Double, Double>>();
+ HashMap<Percept, Pair<Double, Double>> newContextDimensionsBis = new HashMap<Percept, Pair<Double, Double>>();
+ Double center;
+ double length = increment;
+
+ if (overlapDistance(overlappingContextRanges) > nonOverlapDistance(overlappingContextRanges)) {
+
+ if (Math.abs(end - border) > Math.abs(border - start)) {
+ center = (end - increment + end) / 2;
+ } else {
+ center = (start + increment + start) / 2;
+ }
+
+ } else {
+ if (Math.abs(end - border) < Math.abs(border - start)) {
+ center = (end - increment + end) / 2;
+ } else {
+ center = (start + increment + start) / 2;
+
+ }
+ }
+
+ if (overlapDistance(overlappingContextRanges) > nonOverlapDistance(overlappingContextRanges)) {
+
+ if (Math.abs(end - border) > Math.abs(border - start)) {
+ adaptEnd(border, increment);
+ } else {
+ adaptStart(border, increment);
+ }
+
+ } else {
+ if (Math.abs(end - border) < Math.abs(border - start)) {
+ adaptEnd(border, increment);
+ } else {
+ adaptStart(border, increment);
+ }
+ }
+
+ // if(this.context.getLocalModel().getCoef()[world.getScheduler().getPercepts().size()]
+ // != 0.0) { // if model
+ newContextDimensions.put(this.percept, new Pair<Double, Double>(center, length));
+ newContextDimensionsBis.put(this.percept, new Pair<Double, Double>(center, length));
+ ArrayList<Pair<Double, Double>> centersAndLengths = new ArrayList<Pair<Double, Double>>();
+ boolean newContext = true;
+
+ for (Percept pct : context.getAmas().getPercepts()) {
+ if (pct != percept) {
+ Context overlappingContext = overlappingContextRanges.getContext();
+ newContext = newContext
+ && !context.getRanges().get(pct).containedBy(overlappingContext.getRanges().get(pct));
+
+ if (newContext) {
+
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList(this.context.getName(), "" + context.getRanges().get(pct),
+ overlappingContext.getRanges().get(pct) + "", pct.getName(), "RANGES")));
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList(this.context.getName(), "" + this.context.getRanges().get(pct).getLenght(),
+ this.context.getRanges().get(pct)
+ .overlapDistance(overlappingContext.getRanges().get(pct)) + "",
+ pct.getName(), "LENGTHS")));
+
+ centersAndLengths = this.context.getRanges().get(pct)
+ .getCentersAndLengthsOfNonOverlapingZones(overlappingContext.getRanges().get(pct));
+ if (centersAndLengths.isEmpty()) {
+ newContext = false;
+ } else if (centersAndLengths.size() == 1) {
+ newContextDimensions.put(pct, new Pair<Double, Double>(centersAndLengths.get(0).getA(),
+ centersAndLengths.get(0).getB()));
+ } else if (centersAndLengths.size() == 2) {
+ newContextDimensions.put(pct, new Pair<Double, Double>(centersAndLengths.get(0).getA(),
+ centersAndLengths.get(0).getB()));
+ newContextDimensionsBis.put(pct, new Pair<Double, Double>(centersAndLengths.get(1).getA(),
+ centersAndLengths.get(1).getB()));
+ }
+ }
+ }
+ }
+
+ if (newContext) {
+
+ world.raiseNCS(NCS.CREATE_NEW_CONTEXT);
+ for (Percept pct : context.getAmas().getPercepts()) {
+ world.trace(TRACE_LEVEL.DEBUG,
+ new ArrayList<String>(Arrays.asList(pct.getName(), "" + newContextDimensions.get(pct).getA(),
+ "" + newContextDimensions.get(pct).getB(), "NEW DIM")));
+ }
+ Context context = new Context(this.context.getAmas(), this.getContext(), newContextDimensions);
+
+ if (centersAndLengths.size() == 2) {
+ world.raiseNCS(NCS.CREATE_NEW_CONTEXT);
+ for (Percept pct : context.getAmas().getPercepts()) {
+ System.out.println("TEST");
+ System.out.println(newContextDimensionsBis.get(pct).getA());
+ System.out.println(newContextDimensionsBis.get(pct).getB());
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList(pct.getName(), "" + newContextDimensionsBis.get(pct).getA(),
+ "" + newContextDimensionsBis.get(pct).getB(), "NEW DIM")));
+ }
+ Context contextBis = new Context(this.context.getAmas(), this.getContext(), newContextDimensionsBis);
+ }
+ }
+ // }
+
+ }
+
+ public void setOnConcurentOverlap(Range overlappingContextRanges, double border) {
+
+ world.trace(TRACE_LEVEL.EVENT, new ArrayList<String>(Arrays.asList(this.context.getName(), percept.getName(),
+ "*********************************************************************************************************** SET ON OVERLAP")));
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList(this.context.getName(), overlappingContextRanges.getContext().getName())));
+
+ double increment = Math.min(Math.abs(this.distance(overlappingContextRanges)), getIncrement());
+
+ HashMap<Percept, Pair<Double, Double>> newContextDimensions = new HashMap<Percept, Pair<Double, Double>>();
+ HashMap<Percept, Pair<Double, Double>> newContextDimensionsBis = new HashMap<Percept, Pair<Double, Double>>();
+ Double center;
+ double length;
+
+ if (overlapDistance(overlappingContextRanges) > nonOverlapDistance(overlappingContextRanges)) {
+
+ if (Math.abs(end - border) > Math.abs(border - start)) {
+ center = (border + end) / 2;
+ length = Math.abs(end - border);
+ } else {
+ center = (start + border) / 2;
+ length = Math.abs(start - border);
+ }
+
+ } else {
+ if (Math.abs(end - border) < Math.abs(border - start)) {
+ center = (border + end) / 2;
+ length = Math.abs(end - border);
+ } else {
+ center = (start + border) / 2;
+ length = Math.abs(start - border);
+
+ }
+ }
+
+ if (overlapDistance(overlappingContextRanges) > nonOverlapDistance(overlappingContextRanges)) {
+
+ if (Math.abs(end - border) > Math.abs(border - start)) {
+ setEnd(border);
+ } else {
+ setStart(border);
+ }
+
+ } else {
+ if (Math.abs(end - border) < Math.abs(border - start)) {
+ setEnd(border);
+ } else {
+ setStart(border);
+ }
+ }
+
+ // if(this.context.getLocalModel().getCoef()[world.getScheduler().getPercepts().size()]
+ // != 0.0) { // if model
+ newContextDimensions.put(this.percept, new Pair<Double, Double>(center, length));
+ newContextDimensionsBis.put(this.percept, new Pair<Double, Double>(center, length));
+ ArrayList<Pair<Double, Double>> centersAndLengths = new ArrayList<Pair<Double, Double>>();
+ boolean newContext = true;
+
+ for (Percept pct : context.getAmas().getPercepts()) {
+ if (pct != percept) {
+ Context overlappingContext = overlappingContextRanges.getContext();
+ newContext = newContext
+ && !context.getRanges().get(pct).containedBy(overlappingContext.getRanges().get(pct));
+
+ if (newContext) {
+
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList(this.context.getName(), "" + context.getRanges().get(pct),
+ overlappingContext.getRanges().get(pct) + "", pct.getName(), "RANGES")));
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList(this.context.getName(), "" + this.context.getRanges().get(pct).getLenght(),
+ this.context.getRanges().get(pct)
+ .overlapDistance(overlappingContext.getRanges().get(pct)) + "",
+ pct.getName(), "LENGTHS")));
+
+ centersAndLengths = this.context.getRanges().get(pct)
+ .getCentersAndLengthsOfNonOverlapingZones(overlappingContext.getRanges().get(pct));
+ if (centersAndLengths.isEmpty()) {
+ newContext = false;
+ } else if (centersAndLengths.size() == 1) {
+ newContextDimensions.put(pct, new Pair<Double, Double>(centersAndLengths.get(0).getA(),
+ centersAndLengths.get(0).getB()));
+ } else if (centersAndLengths.size() == 2) {
+ newContextDimensions.put(pct, new Pair<Double, Double>(centersAndLengths.get(0).getA(),
+ centersAndLengths.get(0).getB()));
+ newContextDimensionsBis.put(pct, new Pair<Double, Double>(centersAndLengths.get(1).getA(),
+ centersAndLengths.get(1).getB()));
+ }
+ }
+ }
+ }
+
+ if (newContext) {
+
+ world.raiseNCS(NCS.CREATE_NEW_CONTEXT);
+ for (Percept pct : context.getAmas().getPercepts()) {
+ world.trace(TRACE_LEVEL.DEBUG,
+ new ArrayList<String>(Arrays.asList(pct.getName(), "" + newContextDimensions.get(pct).getA(),
+ "" + newContextDimensions.get(pct).getB(), "NEW DIM")));
+ }
+ Context context = new Context(this.context.getAmas(), this.getContext(), newContextDimensions);
+
+ if (centersAndLengths.size() == 2) {
+
+ world.raiseNCS(NCS.CREATE_NEW_CONTEXT);
+ for (Percept pct : this.context.getAmas().getPercepts()) {
+ System.out.println("TEST");
+ System.out.println(newContextDimensionsBis.get(pct).getA());
+ System.out.println(newContextDimensionsBis.get(pct).getB());
+
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList(pct.getName(), "" + newContextDimensionsBis.get(pct).getA(),
+ "" + newContextDimensionsBis.get(pct).getB(), "NEW DIM")));
+ }
+ Context contextBis = new Context(this.context.getAmas(), this.getContext(), newContextDimensionsBis);
+ }
+ }
+ // }
+
+ }
+
+ public boolean containedBy(Range range) {
+ return range.getStart() <= this.getStart() && this.getEnd() <= range.getEnd();
+ }
+
+ public ArrayList<Pair<Double, Double>> getCentersAndLengthsOfNonOverlapingZones(Range overlappingRange) {
+
+ ArrayList<Pair<Double, Double>> centersAndLengths = new ArrayList<Pair<Double, Double>>();
+
+ world.trace(TRACE_LEVEL.EVENT, new ArrayList<String>(
+ Arrays.asList(this.context.getName(), overlappingRange.getContext().getName(), "SEEK NON OVERLAPING")));
+
+ if (this.getStart() < overlappingRange.getStart() && overlappingRange.getEnd() < this.getEnd()) {
+
+ world.trace(TRACE_LEVEL.STATE, new ArrayList<String>(Arrays.asList("CONTAINED", this.percept.getName())));
+ double center1 = (this.getStart() + overlappingRange.getStart()) / 2;
+ double center2 = (overlappingRange.getEnd() + this.getEnd()) / 2;
+ double length1 = overlappingRange.getStart() - this.getStart();
+ double length2 = this.getEnd() - overlappingRange.getEnd();
+ centersAndLengths.add(new Pair<Double, Double>(center1, length1));
+ centersAndLengths.add(new Pair<Double, Double>(center2, length2));
+ } else if (this.getStart() < overlappingRange.getStart() && overlappingRange.getStart() < this.getEnd()) {
+
+ world.trace(TRACE_LEVEL.STATE, new ArrayList<String>(Arrays.asList("START", this.percept.getName())));
+ double center = (this.getStart() + overlappingRange.getStart()) / 2;
+ double length = overlappingRange.getStart() - this.getStart();
+ centersAndLengths.add(new Pair<Double, Double>(center, length));
+ } else if (this.getStart() < overlappingRange.getEnd() && overlappingRange.getEnd() < this.getEnd()) {
+
+ world.trace(TRACE_LEVEL.STATE, new ArrayList<String>(Arrays.asList("END", this.percept.getName())));
+ double center = (overlappingRange.getEnd() + this.getEnd()) / 2;
+ double length = this.getEnd() - overlappingRange.getEnd();
+ centersAndLengths.add(new Pair<Double, Double>(center, length));
+ }
+
+ return centersAndLengths;
+
+ }
+
+ private void matchBorderOnOverlap(Range bestContextRanges, double border) {
+
+ if (overlapDistance(bestContextRanges) > nonOverlapDistance(bestContextRanges)) {
+
+ if (Math.abs(end - border) > Math.abs(border - start)) {
+ setEnd(border);
+ } else {
+ setStart(border);
+ }
+
+ } else {
+ if (Math.abs(end - border) < Math.abs(border - start)) {
+ setEnd(border);
+ } else {
+ setStart(border);
+ }
+ }
+
+ }
+
+ /**
+ * Contains.
+ *
+ * @param d : the value to test
+ * @return -1 if lower, +1 if higher, 0 if contained
+ */
+ public int contains(Double d) {
+ if ((d > start || (d >= start && start_inclu)) && (d < end || (d <= end && end_inclu))) {
+ return 0;
+ } else if (d <= start) {
+ return -1;
+ } else {
+ return 1;
+ }
+ }
+
+ /**
+ * Compare to.
+ *
+ * @param i the i
+ * @return the int
+ */
+ public int compareTo(Range i) {
+ // TODO
+
+ if (i.getStart() > this.getStart())
+ return -1;
+ if (i.getStart() < this.getStart())
+ return 1;
+ if (i.getStart() == this.getStart()) {
+ if (i.isStart_inclu() == this.isStart_inclu()) {
+ return 0;
+ } else if (i.isStart_inclu()) {
+ return 1;
+ } else {
+ return -1;
+ }
+ }
+ return 0;
+
+ }
+
+ /**
+ * Gets the alpha factor.
+ *
+ * @return the alpha factor
+ */
+ public double getAlphaFactor() {
+ return alphaFactor;
+ }
+
+ /**
+ * Sets the alpha factor.
+ *
+ * @param alphaFactor the new alpha factor
+ */
+ public void setAlphaFactor(double alphaFactor) {
+ this.alphaFactor = alphaFactor;
+ }
+
+ /**
+ * Checks if is end inclu.
+ *
+ * @return true, if is end inclu
+ */
+ public boolean isEnd_inclu() {
+ return end_inclu;
+ }
+
+ /**
+ * Sets the end inclu.
+ *
+ * @param end_inclu the new end inclu
+ */
+ public void setEnd_inclu(boolean end_inclu) {
+ this.end_inclu = end_inclu;
+ }
+
+ /**
+ * Checks if is start inclu.
+ *
+ * @return true, if is start inclu
+ */
+ public boolean isStart_inclu() {
+ return start_inclu;
+ }
+
+ /**
+ * Sets the start inclu.
+ *
+ * @param start_inclu the new start inclu
+ */
+ public void setStart_inclu(boolean start_inclu) {
+ this.start_inclu = start_inclu;
+ }
+
+ /**
+ * Gets the lenght.
+ *
+ * @return length of the range.
+ */
+ public double getLenght() {
+ return end - start;
+ }
+
+ /**
+ * Sets the minimum size.
+ *
+ * @param v the new minimum size
+ */
+ public void setMinimumSize(Percept v) {
+ if (getLenght() < v.getMinMaxDistance() * Range.minLenghtRatio) {
+ double distanceToAdd = (v.getMinMaxDistance() * Range.minLenghtRatio) - getLenght();
+ this.setStart(start - (distanceToAdd / 2.0));
+ this.setEnd(end + (distanceToAdd / 2.0));
+ }
+ }
+
+ /**
+ * Add a margin based on a percentage of the lenght of the range.
+ *
+ * @param percent : percentage of the length
+ */
+ private void addMargin(double percent) {
+ this.setStart(start - (this.getLenght() * percent));
+ this.setEnd(end + (this.getLenght() * percent));
+ }
+
+ /**
+ * Gets the nearest limit.
+ *
+ * @param d the d
+ * @return End is true, start is false
+ */
+ public boolean getNearestLimit(double d) {
+ return (Math.abs(d - start) < Math.abs(end - d)) ? false : true;
+ }
+
+ /**
+ * Gets the start.
+ *
+ * @return the start
+ */
+ public double getStart() {
+ return start;
+ }
+
+ /**
+ * Gets the end.
+ *
+ * @return the end
+ */
+ public double getEnd() {
+ return end;
+ }
+
+ public double getRange(String rangeType) {
+ if (rangeType.equals("start")) {
+ return start;
+ } else if (rangeType.equals("end")) {
+ return end;
+ } else {
+ return 0d;
+ }
+ }
+
+ /**
+ * Gets the value.
+ *
+ * @return the value
+ */
+ public double getValue() {
+ return value;
+ }
+
+ /**
+ * Sets the value.
+ *
+ * @param value the new value
+ */
+ public void setValue(double value) {
+ this.oldValue = this.value;
+ this.value = value;
+ }
+
+ /**
+ * Checks if is percept enum.
+ *
+ * @return true, if is percept enum
+ */
+ public boolean isPerceptEnum() {
+ return percept.isEnum();
+ }
+
+ /*
+ * (non-Javadoc)
+ *
+ * @see java.lang.Comparable#compareTo(java.lang.Object)
+ */
+ @Override
+ public int compareTo(Object o) {
+ return this.compareTo(o);
+ }
+
+ public void setStart(double newStartValue) {
+
+ if (context != null && percept != null) {
+ ////// System.out.println(context.getName() + " " + percept.getName() + " START
+ ////// " + (Math.abs(newStartValue-this.start)));
+ }
+
+// if ((Double) newStartValue != null) {
+// if (newStartValue < percept.getMin()) {
+// this.start = percept.getMin();
+//
+// } else {
+// this.start = newStartValue;
+// }
+// } else {
+// this.start = newStartValue;
+// }
+
+ this.start = newStartValue;
+
+
+
+ if (this.context != null) {
+
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList(this.context.getName(), this.percept.getName(), "SET START", "" + newStartValue)));
+
+ lastStartTickModification = this.context.getAmas().getCycle();
+ this.percept.updateContextProjectionStart(this.context);
+ context.getAmas().addLastmodifiedContext(context);
+
+ if (!this.context.isDying() && !context.getAmas().getSpatiallyAlteredContextForUnityUI().contains(this.context)) {
+ context.getAmas().addSpatiallyAlteredContextForUnityUI(this.context);
+ }
+ }
+
+ // NCSDetection_Uselessness();
+
+ }
+
+ public void setEnd(double newEndValue) {
+
+ if (context != null && percept != null) {
+ ////// System.out.println(context.getName() + " " + percept.getName() + " END "
+ ////// + (Math.abs(newEndValue-this.end)));
+ }
+// if ((Double) newEndValue != null) {
+// if (newEndValue > percept.getMax()) {
+// this.end = percept.getMax();
+// } else {
+// this.end = newEndValue;
+// }
+// } else {
+// this.end = newEndValue;
+// }
+
+ this.end = newEndValue;
+
+
+ if (this.context != null) {
+ world.trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(
+ Arrays.asList(this.context.getName(), this.percept.getName(), "SET END", "" + newEndValue)));
+
+ lastEndTickModification = context.getAmas().getCycle();
+ this.percept.updateContextProjectionEnd(this.context);
+ context.getAmas().addLastmodifiedContext(context);
+
+ if (!this.context.isDying() && !context.getAmas().getSpatiallyAlteredContextForUnityUI().contains(this.context)) {
+ context.getAmas().addSpatiallyAlteredContextForUnityUI(this.context);
+ }
+ }
+
+ // NCSDetection_Uselessness();
+ }
+
+ public void NCSDetection_Uselessness() {
+ if (context != null) {
+ if (this.isTooSmall()) {
+ context.solveNCS_Uselessness();
+ }
+ }
+
+ }
+
+ public boolean contains(Double value, Double neighborhood) {
+ //// System.out.println(context.getName() +" "+ percept.getName() + " " + value
+ //// + " " + (start - neighborhood) + " " + start + " " + end + " " + (end +
+ //// neighborhood));
+ return Math.abs(value - getCenter()) < (getRadius() + neighborhood);
+ }
+
+ public boolean contains2(Double value) {
+ return Math.abs(value - getCenter()) <= getRadius();
+ }
+
+ public Range clone() throws CloneNotSupportedException {
+ return (Range) super.clone();
+ }
+
+ public double getCenter() {
+ return (end + start) / 2;
+ }
+
+ public double getRadius() {
+ return (end - start) / 2;
+ }
+
+ public int getLastStartTickModification() {
+ return lastStartTickModification;
+ }
+
+ public int getLastEndTickModification() {
+ return lastEndTickModification;
+ }
+
+ public double distance(Range otherRange) {
+ return Math.abs(this.getCenter() - otherRange.getCenter()) - this.getRadius() - otherRange.getRadius();
+ }
+
+ public double distanceForVolume(Range otherRange) {
+ double centerDistance = Math.abs(this.getCenter() - otherRange.getCenter());
+
+ if (centerDistance + otherRange.getRadius() < this.getRadius()) {
+ return otherRange.getRadius() * 2;
+ } else if (centerDistance + this.getRadius() < otherRange.getRadius()) {
+ return this.getRadius() * 2;
+ } else {
+ return centerDistance - this.getRadius() - otherRange.getRadius();
+ }
+
+ }
+
+ public double distanceForMaxOrMin(Range otherRange) {
+ double centerDistance = Math.abs(this.getCenter() - otherRange.getCenter());
+
+ if ((centerDistance + otherRange.getRadius() < this.getRadius())
+ || (centerDistance + this.getRadius() < otherRange.getRadius())) {
+ return 0.0;
+ } else {
+ return centerDistance - this.getRadius() - otherRange.getRadius();
+ }
+
+ }
+
+ public double startDistance(Range otherRange) {
+ return Math.abs(this.getStart() - otherRange.getEnd());
+ }
+
+ public double endDistance(Range otherRange) {
+ return Math.abs(this.getEnd() - otherRange.getStart());
+ }
+
+ public double startDistance(double value) {
+ return Math.abs(this.getStart() - value);
+ }
+
+ public double endDistance(double value) {
+ return Math.abs(this.getEnd() - value);
+ }
+
+ public double distance(double value) {
+ return Math.abs(this.getCenter() - value) - this.getRadius();
+ }
+
+ public double centerDistance(double value) {
+ return value - this.getCenter();
+ }
+
+ public double overlapDistance(Range otherRange) {
+
+ double distanceBetweenRanges = distance(otherRange);
+ if (distanceBetweenRanges < 0) {
+ return Math.abs(distanceBetweenRanges);
+ } else {
+ return 0.0;
+ }
+ }
+
+ private double nonOverlapDistance(Range otherRange) {
+ return this.getLenght() - overlapDistance(otherRange);
+ }
+
+ private double voidDistance(Range otherRange) {
+
+ double distanceBetweenRanges = distance(otherRange);
+ if (distanceBetweenRanges > 0) {
+ return distanceBetweenRanges;
+ } else {
+ return 0.0;
+ }
+ }
+
+ public boolean inNeighborhood() {
+ return this.contains(percept.getValue(), context.getEnvironment().getContextCreationNeighborhood(context, percept))
+ || this.contains(percept.getValue(), context.getEnvironment().getContextCreationNeighborhood(context, percept));
+ }
+
+}
diff --git a/AMOEBAonAMAK/src/agents/context/SpatialContext.java b/AMOEBAonAMAK/src/agents/context/SpatialContext.java
new file mode 100644
index 0000000000000000000000000000000000000000..69538fe12db4112690e32a98c5291b6affb0a4e4
--- /dev/null
+++ b/AMOEBAonAMAK/src/agents/context/SpatialContext.java
@@ -0,0 +1,77 @@
+package agents.context;
+
+import java.util.HashMap;
+
+import utils.Pair;
+import agents.percept.Percept;
+
+public class SpatialContext {
+
+ private HashMap<Percept, Pair<Double, Double>> ranges = new HashMap<Percept, Pair<Double, Double>>();
+
+
+
+ public SpatialContext(Context ctxt) {
+
+ for(Percept pct : ctxt.getRanges().keySet()) {
+ ranges.put(pct, new Pair<Double, Double>(ctxt.getRanges().get(pct).getStart(), ctxt.getRanges().get(pct).getEnd()));
+ }
+
+ }
+
+ public void setRange(Percept pct, Pair<Double, Double> range) {
+ ranges.put(pct, range);
+ }
+
+ public Pair<Double, Double> getRange(Percept pct){
+ return ranges.get(pct);
+ }
+
+
+ public double getVolume() {
+ double volume = 1.0;
+ for(Percept pct : ranges.keySet()) {
+ volume *= 2*getRadius(pct);
+ }
+ return volume;
+ }
+
+ public double getRadius(Percept pct) {
+ return Math.abs(getEnd(pct) - getStart(pct))/2;
+ }
+
+ public double getCenter(Percept pct) {
+ return (getEnd(pct) + getStart(pct))/2;
+ }
+
+ public double getEnd(Percept pct) {
+ return ranges.get(pct).getB();
+ }
+
+ public void setEnd(Percept pct, double value) {
+ ranges.get(pct).setB(value);
+ }
+
+ public void expandEnd(Percept pct, double value) {
+ ranges.get(pct).setB(getEnd(pct) + value);
+ }
+
+ public double getStart(Percept pct) {
+ return ranges.get(pct).getA();
+ }
+
+ public void setStart(Percept pct, double value) {
+ ranges.get(pct).setA(value);
+ }
+
+ public void expandStart(Percept pct, double value) {
+ ranges.get(pct).setA(getStart(pct) - value);
+ }
+
+ public double distance(Percept pct, Range otherRange) {
+
+ return Math.abs(this.getCenter(pct) - otherRange.getCenter()) - this.getRadius(pct) - otherRange.getRadius();
+ }
+}
+
+
diff --git a/AMOEBAonAMAK/src/agents/context/localModel/LocalModel.java b/AMOEBAonAMAK/src/agents/context/localModel/LocalModel.java
index 41e134242b3ad1c523e494e547ed85ffeef16764..2aab80c87bae8e396c3e7eaec30e4073612fb3b9 100644
--- a/AMOEBAonAMAK/src/agents/context/localModel/LocalModel.java
+++ b/AMOEBAonAMAK/src/agents/context/localModel/LocalModel.java
@@ -1,59 +1,110 @@
-package agents.context.localModel;
-
-import agents.context.Context;
-import agents.percept.Percept;
-
-/**
- * The abstract class of all agents in charge of the generation of the output
- * from Context Agent. For the sake of simplicity, it's not scheduled as agent
- * like other of the system.
- */
-public abstract class LocalModel {
-
- /**
- * Instantiates a new local model agent.
- */
- public LocalModel() {
- }
-
- /**
- * Update model.
- *
- * @param context the context
- */
- public abstract void updateModel(Context context);
-
- /**
- * Gets the proposition.
- *
- * @param context the context
- * @return the proposition
- */
- public abstract double getProposition(Context context);
-
- /**
- * Version of getProposition for 2D display.
- *
- * @param context the context
- * @param p1 the p 1
- * @param p2 the p 2
- * @param v1 the v 1
- * @param v2 the v 2
- * @return the proposition
- */
- public abstract double getProposition(Context context, Percept p1, Percept p2, double v1, double v2);
-
- /**
- * Gets the formula.
- *
- * @param context the context
- * @return the formula
- */
- public abstract String getFormula(Context context);
-
- public abstract String getCoefsFormula();
-
- public abstract double[] getCoefs();
-
- public abstract TypeLocalModel getType();
-}
+package agents.context.localModel;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+
+import agents.context.Context;
+import agents.context.Experiment;
+
+/**
+ * A LocalModel is used by a Context to store information and generate prediction.
+ */
+public interface LocalModel {
+
+ /**
+ * Sets the context that use the LocalModel
+ * @param context
+ */
+ public void setContext(Context context);
+
+ /**
+ * gets the context that use the LocalModel
+ * @return
+ */
+ public Context getContext();
+
+ /**
+ * Gets the proposition.
+ *
+ * @return the proposition
+ */
+ public double getProposition();
+
+ /**
+ * Gets the proposition with the highest value possible
+ * @return
+ */
+ public double getMaxProposition();
+
+ /**
+ * Return the point (percept value) that produce the max proposition, considering some percepts are fixed.
+ * @return a HashMap with percept names as key, and their corresponding value. The oracle is the max proposition
+ * @see LocalModel#getMaxProposition(Context)
+ */
+ public HashMap<String, Double> getMaxWithConstraint(HashMap<String, Double> fixedPercepts);;
+
+ /**
+ * Gets the proposition with the lowest value possible
+ * @return
+ */
+ public double getMinProposition();
+
+ /**
+ * Gets the formula of the model
+ * @return
+ */
+ public String getCoefsFormula();
+
+ /**
+ * Update the model with a new experiment.
+ * @param newExperiment
+ * @param weight the weight of the new experiment in the compute of the model
+ */
+ public void updateModel(Experiment newExperiment, double weight);
+
+ public String coefsToString();
+
+ /**
+ * The distance between an experiment and the model.
+ * @param experiment
+ * @return
+ */
+ public double distance(Experiment experiment);
+
+ /**
+ * Gets the experiments used to properly initialize the model.
+ * @return
+ */
+ public ArrayList<Experiment> getFirstExperiments();
+
+ /**
+ * Sets the experiments used to properly initialize the model.
+ * This may not trigger an update of the model.
+ * @param frstExp
+ */
+ public void setFirstExperiments( ArrayList<Experiment> frstExp);
+
+ /**
+ * Tells if the model has enough experiments to produce a good prediction.
+ * For example, a regression need a number of experiments equals or superior to the number of dimension.
+ * @return
+ */
+ public boolean finishedFirstExperiments();
+
+ /**
+ * Gets coefficients of the model
+ * @return
+ */
+ public Double[] getCoef();
+
+ /**
+ * Sets coefficients of the model
+ * @return
+ */
+ public void setCoef(Double[] coef);
+
+ /**
+ * Gets the {@link TypeLocalModel} corresponding to this LocalModel
+ */
+ public TypeLocalModel getType();
+}
diff --git a/AMOEBAonAMAK/src/agents/context/localModel/LocalModelAverage.java b/AMOEBAonAMAK/src/agents/context/localModel/LocalModelAverage.java
deleted file mode 100644
index 27720e044072b41ad731389ea3825b6c1dcdca25..0000000000000000000000000000000000000000
--- a/AMOEBAonAMAK/src/agents/context/localModel/LocalModelAverage.java
+++ /dev/null
@@ -1,47 +0,0 @@
-package agents.context.localModel;
-
-import agents.context.Context;
-import agents.context.Experiment;
-import agents.percept.Percept;
-
-/**
- * A simple local model which computes the average of all Context Agents
- * experiments.
- *
- */
-public class LocalModelAverage extends LocalModel {
-
- @Override
- public void updateModel(Context context) {
- }
-
- public double getProposition(Context context) {
- double average = 0.0;
- for (Experiment exp : context.getExperiments()) {
- average += exp.getProposition();
- }
- return average / context.getExperiments().size();
- }
-
- public double getProposition(Context context, Percept p1, Percept p2, double v1, double v2) {
- return 0;
- }
-
- public String getFormula(Context context) {
- return getProposition(context) + "";
- }
-
- public String getCoefsFormula() {
- return "";
- }
-
- @Override
- public double[] getCoefs() {
- return new double[1];
- }
-
- @Override
- public TypeLocalModel getType() {
- return TypeLocalModel.AVERAGE;
- }
-}
diff --git a/AMOEBAonAMAK/src/agents/context/localModel/LocalModelFirstExp.java b/AMOEBAonAMAK/src/agents/context/localModel/LocalModelFirstExp.java
deleted file mode 100644
index f658955cdff0fcea6dc3ef084746b951f36e1d9b..0000000000000000000000000000000000000000
--- a/AMOEBAonAMAK/src/agents/context/localModel/LocalModelFirstExp.java
+++ /dev/null
@@ -1,54 +0,0 @@
-package agents.context.localModel;
-
-import agents.context.Context;
-import agents.percept.Percept;
-
-/**
- * A simple local model which uses only the value of the first experiment.
- * Useful for output like integer.
- *
- */
-public class LocalModelFirstExp extends LocalModel {
-
- /**
- * Instantiates a new local model first exp.
- *
- * @param world the world
- */
- public LocalModelFirstExp() {
-
- }
-
- @Override
- public void updateModel(Context context) {
- }
-
- @Override
- public double getProposition(Context context) {
- return context.getExperiments().get(0).getProposition();
- }
-
- @Override
- public double getProposition(Context context, Percept p1, Percept p2, double v1, double v2) {
- return 0;
- }
-
- @Override
- public String getFormula(Context context) {
- return context.getExperiments().get(0).getProposition() + "";
- }
-
- public String getCoefsFormula() {
- return "";
- }
-
- @Override
- public double[] getCoefs() {
- return new double[1];
- }
-
- @Override
- public TypeLocalModel getType() {
- return TypeLocalModel.FIRST_EXPERIMENT;
- }
-}
diff --git a/AMOEBAonAMAK/src/agents/context/localModel/LocalModelMillerRegression.java b/AMOEBAonAMAK/src/agents/context/localModel/LocalModelMillerRegression.java
index 64ca2ff62ba0331a10d691d672d6d170c3340272..09e8863819aa2a36fcb0d8d9d4896a2bc36979e3 100644
--- a/AMOEBAonAMAK/src/agents/context/localModel/LocalModelMillerRegression.java
+++ b/AMOEBAonAMAK/src/agents/context/localModel/LocalModelMillerRegression.java
@@ -1,175 +1,503 @@
-package agents.context.localModel;
-
-import java.util.ArrayList;
-
-import agents.context.Context;
-import agents.context.Experiment;
-import agents.percept.Percept;
-
-/**
- * The Class LocalModelMillerRegression.
- */
-public class LocalModelMillerRegression extends LocalModel {
-
- /** The n parameters. */
- private int nParameters;
-
- /** The regression. */
- transient private Regression regression;
-
- /** The coefs. */
- private double[] coefs;
-
- /**
- * Instantiates a new local model miller regression.
- *
- * @param world the world
- */
- public LocalModelMillerRegression(int nParameters) {
- this.nParameters = nParameters;
- this.regression = new Regression(nParameters, true);
- }
-
- @Override
- public void updateModel(Context context) {
- regression = new Regression(nParameters, true);
- for (Experiment exp : context.getExperiments()) {
- regression.addObservation(exp.getValuesAsArray(), exp.getProposition());
- }
-
- // TODO : to improve
- while (regression.getN() < context.getExperiments().get(0).getValues().size() + 2) {
- regression.addObservation(context.getExperiments().get(0).getValuesAsArray(),
- context.getExperiments().get(0).getProposition());
- }
-
- coefs = regression.regress().getParameterEstimates();
- }
-
- public void setCoefs(double[] coefs) {
- this.coefs = coefs;
- }
-
- /**
- * Gets the coefficients
- *
- * @return the coefs
- */
- public double[] getCoefs() {
- return coefs;
- }
-
- public double getProposition(Context context) {
- ArrayList<Percept> percepts = context.getAmas().getPercepts();
-
- if (context.getExperiments().size() == 1) {
- return context.getExperiments().get(0).getProposition();
- }
-
- double result = coefs[0];
- if (coefs[0] == Double.NaN)
- System.exit(0);
- for (int i = 1; i < coefs.length; i++) {
- if (Double.isNaN(coefs[i]))
- coefs[i] = 0;
- result += coefs[i] * percepts.get(i - 1).getValue();
- }
-
- return result;
- }
-
- public double getProposition(Context context, Percept p1, Percept p2, double v1, double v2) {
-
- if (context.getExperiments().size() == 1) {
- return context.getExperiments().get(0).getProposition();
- }
-
- regression = new Regression(nParameters, true);
- for (Experiment exp : context.getExperiments()) {
- regression.addObservation(exp.getValuesAsArray(), exp.getProposition());
-
- // TODO : to improve
- while (regression.getN() < context.getExperiments().get(0).getValues().size() + 2) {
- regression.addObservation(context.getExperiments().get(0).getValuesAsArray(),
- context.getExperiments().get(0).getProposition());
- }
- }
-
- double[] coef = regression.regress().getParameterEstimates();
-
- double[] tabv = { v1, v2 };
-
- double result = coef[0];
- if (coef[0] == Double.NaN)
- System.exit(0);
- for (int i = 1; i < coef.length; i++) {
- if (Double.isNaN(coef[i]))
- coef[i] = 0;
- result += coef[i] * tabv[i - 1];
- }
- return result;
-
- }
-
- public String getFormula(Context context) {
- String s = "";
- if (context.getExperiments().size() == 1) {
- return "" + context.getExperiments().get(0).getProposition();
- } else {
- if (regression == null) {
- updateModel(context);
- }
- double[] coef = regression.regress().getParameterEstimates();
-
- ArrayList<Percept> percepts = context.getAmas().getPercepts();
-
- if (coef[0] == Double.NaN)
- System.exit(0);
- for (int i = 1; i < coef.length; i++) {
- if (Double.isNaN(coef[i]))
- coef[i] = 0;
- s += coef[i] + "*" + percepts.get(i - 1).getName();
-
- if (i < coef.length - 1)
- s += " + ";
- }
-
- s += "\n with ";
-
- for (int i = 1; i < coef.length; i++) {
- if (Double.isNaN(coef[i]))
- coef[i] = 0;
- s += percepts.get(i - 1).getName() + " = " + percepts.get(i - 1).getValue();
- s += ", ";
- }
-
- s += "\n with ";
- s += context.getExperiments().size() + " experimentations";
-
- s += "\n with ";
- s += getProposition(context) + " as result";
-
- return s;
- }
-
- }
-
- public String getCoefsFormula() {
- String result = "" + coefs[0];
- if (coefs[0] == Double.NaN)
- System.exit(0);
-
- for (int i = 1; i < coefs.length; i++) {
- if (Double.isNaN(coefs[i]))
- coefs[i] = 0;
-
- result += "\t" + coefs[i];
- }
- return result;
- }
-
- @Override
- public TypeLocalModel getType() {
- return TypeLocalModel.MILLER_REGRESSION;
- }
-}
+package agents.context.localModel;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.HashMap;
+import java.util.List;
+
+import agents.context.Context;
+import agents.context.Experiment;
+import agents.percept.Percept;
+import utils.Pair;
+import utils.TRACE_LEVEL;
+
+/**
+ * The Class LocalModelMillerRegression.
+ */
+public class LocalModelMillerRegression implements LocalModel{
+
+ private Context context;
+
+ /** The n parameters. */
+ private int nParameters;
+
+ /** The regression. */
+ transient private Regression regression;
+
+
+ /** The coef. */
+ private Double[] coefs;
+
+ private ArrayList<Experiment> firstExperiments;
+
+ /**
+ * Instantiates a new local model miller regression.
+ *
+ * @param world the world
+ */
+ public LocalModelMillerRegression(Context associatedContext) {
+ context = associatedContext;
+ ArrayList<Percept> var = associatedContext.getAmas().getPercepts();
+ this.nParameters = var.size();
+ regression = new Regression(nParameters,true);
+ firstExperiments = new ArrayList<Experiment>();
+ }
+
+ public LocalModelMillerRegression(Context associatedContext, Double[] coefsCopy, List<Experiment> fstExperiments) {
+ context = associatedContext;
+ ArrayList<Percept> var = associatedContext.getAmas().getPercepts();
+ this.nParameters = var.size();
+ regression = new Regression(nParameters,true);
+ coefs = coefsCopy;
+ firstExperiments = new ArrayList<Experiment>(fstExperiments);
+ }
+
+ @Override
+ public void setContext(Context context) {
+ this.context = context;
+ }
+
+ @Override
+ public Context getContext() {
+ return context;
+ }
+
+ /**
+ * Sets the coef.
+ *
+ * @param coef the new coef
+ */
+ @Override
+ public void setCoef(Double[] coef) {
+ this.coefs = coef.clone();
+ }
+
+ /**
+ * Gets the coef.
+ *
+ * @return the coef
+ */
+ @Override
+ public Double[] getCoef() {
+ return coefs;
+ }
+
+ @Override
+ public double getProposition() {
+
+ ArrayList<Percept> percepts = context.getAmas().getPercepts();
+
+
+
+ double result = coefs[0];
+
+ if (coefs[0] == Double.NaN) System.exit(0);
+
+ for (int i = 1 ; i < coefs.length ; i++) {
+
+ if (Double.isNaN(coefs[i])) coefs[i] = 0.0;
+ result += coefs[i] * percepts.get(i-1).getValue();
+
+ }
+
+ return result;
+ }
+
+
+
+ private double getProposition(Context context, double[] situation) {
+
+ double result = coefs[0];
+
+ if (coefs[0] == Double.NaN) System.exit(0);
+
+ for (int i = 1 ; i < coefs.length ; i++) {
+
+ if (Double.isNaN(coefs[i])) coefs[i] = 0.0;
+ result += coefs[i] * situation[i-1];
+
+ }
+
+ return result;
+ }
+
+ @Override
+ public double getMaxProposition() {
+
+ ArrayList<Percept> percepts = context.getAmas().getPercepts();
+ double result = coefs[0];
+
+ if (coefs[0] == Double.NaN)
+ throw new ArithmeticException("First coeficient of model cannot be NaN");
+
+ for (int i = 1 ; i < coefs.length ; i++) {
+ double coef = coefs[i];
+ if (Double.isNaN(coef)) coef = 0.0;
+ if(coef>0) {
+ result += coef * context.getRanges().get(percepts.get(i-1)).getEnd();
+ }
+ else {
+ result += coef * context.getRanges().get(percepts.get(i-1)).getStart();
+ }
+ }
+
+ return result;
+ }
+
+ @Override
+ public HashMap<String, Double> getMaxWithConstraint(HashMap<String, Double> fixedPercepts){
+ ArrayList<Percept> percepts = context.getAmas().getPercepts();
+
+ HashMap<String, Double> result = new HashMap<String, Double>();
+ result.put("oracle", coefs[0]);
+
+ if (coefs[0] == Double.NaN)
+ throw new ArithmeticException("First coeficient of model cannot be NaN");
+
+ for (int i = 1 ; i < coefs.length ; i++) {
+ double coef = coefs[i];
+ if (Double.isNaN(coef)) coef = 0.0;
+ double pos;
+ Percept p = percepts.get(i-1);
+ if(fixedPercepts.containsKey(p.getName())) {
+ pos = fixedPercepts.get(p.getName());
+ } else {
+ if(coef>0) {
+ pos = context.getRanges().get(p).getEnd();
+ }
+ else {
+ pos = context.getRanges().get(p).getStart();
+ }
+ }
+ double value = coef * pos;
+ result.put("oracle", result.get("oracle") + value);
+ result.put(p.getName(), pos);
+ }
+
+ return result;
+ }
+
+ @Override
+ public double getMinProposition() {
+
+ ArrayList<Percept> percepts = context.getAmas().getPercepts();
+ double result = coefs[0];
+
+ if (coefs[0] == Double.NaN) System.exit(0);
+
+ for (int i = 1 ; i < coefs.length ; i++) {
+
+ if (Double.isNaN(coefs[i])) coefs[i] = 0.0;
+ if(coefs[i]<0) {
+ result += coefs[i] * context.getRanges().get(percepts.get(i-1)).getEnd();
+ }
+ else {
+ result += coefs[i] * context.getRanges().get(percepts.get(i-1)).getStart();
+ }
+ }
+
+ return result;
+ }
+
+ public double getProposition(Experiment experiment) {
+
+ if (coefs[0] == Double.NaN) System.exit(0);
+
+ double result = coefs[0];
+ for (int i = 1 ; i < coefs.length ; i++) {
+
+ if (Double.isNaN(coefs[i])) coefs[i] = 0.0;
+ result += coefs[i] * experiment.getValuesAsArray()[i-1];
+
+ }
+
+ return result;
+
+ }
+
+ @Override
+ public String getCoefsFormula() {
+ String result = "" +coefs[0];
+ // //System.out.println("Result 0" + " : " + result);
+ if (coefs[0] == Double.NaN) System.exit(0);
+
+ for (int i = 1 ; i < coefs.length ; i++) {
+ if (Double.isNaN(coefs[i])) coefs[i] = 0.0;
+
+ result += "\t" + coefs[i] + " (" + context.getAmas().getPercepts().get(i-1) +")";
+
+ }
+
+ return result;
+
+}
+ @Override
+ public void updateModel(Experiment newExperiment, double weight) {
+ context.getAmas().getEnvironment().trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList(context.getName(),"NEW POINT REGRESSION", "FIRST POINTS :", ""+firstExperiments.size(), "OLD MODEL :", coefsToString())));
+
+ if(firstExperiments.size()< (nParameters + 2)) {
+ firstExperiments.add(newExperiment);
+ updateModel();
+
+ }else {
+ updateModelWithExperimentAndWeight(newExperiment, weight, context.getAmas().data.numberOfPointsForRegression);
+ }
+
+ context.getAmas().addSpatiallyAlteredContextForUnityUI(context);
+ context.getAmas().getEnvironment().trace(TRACE_LEVEL.INFORM,new ArrayList<String>(Arrays.asList(context.getName(),"NEW POINT REGRESSION", "FIRST POINTS :", ""+firstExperiments.size(), "MODEL :", coefsToString())));
+ }
+
+ public void updateModel() {
+
+
+ regression = new Regression(nParameters,true);
+
+ for (Experiment exp : firstExperiments) {
+
+ regression.addObservation(exp.getValuesAsArray(), exp.getOracleProposition());
+
+ }
+
+ int i = 0;
+ while (regression.getN() < nParameters + 2) {
+
+ regression.addObservation(firstExperiments.get(i%firstExperiments.size()).getValuesAsArray(), firstExperiments.get(i%firstExperiments.size()).getOracleProposition());
+ i++;
+ }
+
+
+ double[] coef = regression.regress().getParameterEstimates();
+ coefs = new Double[coef.length];
+ for(int j = 0; j < coef.length; j++) {
+ coefs[j] = coef[j];
+ }
+
+ }
+
+
+ public void updateModelWithExperimentAndWeight(Experiment newExperiment, double weight, int numberOfPoints) {
+
+ regression = new Regression(nParameters,true);
+
+
+ int numberOfPointsForRegression = numberOfPoints;
+ if(numberOfPointsForRegression < (nParameters+2)) {
+ numberOfPointsForRegression += numberOfPointsForRegression*((int)((nParameters+2)/numberOfPointsForRegression));
+ }
+
+ Pair<double[][], double[]> artificialSituations = getRandomlyDistributedArtificialExperiments((int)(numberOfPointsForRegression - (numberOfPointsForRegression*weight)));
+ //Pair<double[][], double[]> artificialSituations = getEquallyDistributedArtificialExperiments((int)(numberOfPointsForRegression - (numberOfPointsForRegression*weight)));
+
+
+ int numberOfArtificialPoints = artificialSituations.getB().length;
+ for (int i =0;i<numberOfArtificialPoints;i++) {
+
+ regression.addObservation(artificialSituations.getA()[i], artificialSituations.getB()[i]);
+ }
+
+
+ int numberOfXPPoints;
+ if(numberOfArtificialPoints != (int)(numberOfPointsForRegression - (numberOfPointsForRegression*weight))) {
+ numberOfXPPoints = (int)(weight*numberOfArtificialPoints/(1-weight));
+ }
+ else {
+ numberOfXPPoints = (int)(numberOfPointsForRegression*weight);
+ }
+
+ for (int i =0;i<numberOfXPPoints;i++) {
+
+ regression.addObservation(newExperiment.getValuesAsArray(), newExperiment.getOracleProposition());
+
+
+
+ }
+
+ while (regression.getN() < newExperiment.getValuesAsLinkedHashMap().size() + 2) {
+
+ regression.addObservation(newExperiment.getValuesAsArray(), newExperiment.getOracleProposition());
+
+ System.out.println("ADING Observations " + regression.getN());
+
+ }
+
+
+
+ double[] coef = regression.regress().getParameterEstimates();
+ coefs = new Double[coef.length];
+ for(int i = 0; i < coef.length; i++) {
+ coefs[i] = coef[i];
+ }
+
+ context.getAmas().getEnvironment().regressionPoints = numberOfXPPoints + numberOfArtificialPoints;
+
+
+ }
+
+ private Pair<double[][], double[]> getEquallyDistributedArtificialExperiments(int amount){
+
+
+ int nbPercept = context.getAmas().getPercepts().size();
+
+ int[] nbPointsByPercept = new int[nbPercept];
+
+ ArrayList<Double> pointsByPercept[] = new ArrayList[nbPercept];
+
+ int totalNumberOfPoints = 1;
+
+ for(int i = 0 ; i < nbPercept ; i++) {
+
+ double startRange = this.context.getRanges().get(context.getAmas().getPercepts().get(i)).getStart();
+ double endRange = this.context.getRanges().get(context.getAmas().getPercepts().get(i)).getEnd();
+
+ nbPointsByPercept[i] = (int)(amount*this.context.rangeLengthRatio(context.getAmas().getPercepts().get(i)));
+ pointsByPercept[i] = new ArrayList<Double>();
+
+ totalNumberOfPoints *= nbPointsByPercept[i];
+
+
+ for(int j=0;j<=nbPointsByPercept[i]-1;j++) {
+ pointsByPercept[i].add(startRange + ((endRange-startRange)/(nbPointsByPercept[i]-1))*j );
+ }
+
+ }
+
+ nbPercept = context.getAmas().getPercepts().size();
+ int[] perceptIndices = new int[nbPercept];
+ for(int i = 0 ; i < nbPercept ; i++) {
+ perceptIndices[i] = 0;
+ }
+
+
+ int i = 0;
+ boolean test = true;
+ double[][] artificalExperiments = new double[totalNumberOfPoints][nParameters];
+ double[] artificalResults = new double[totalNumberOfPoints];
+
+ while(test) {
+
+ for(int j = 0;j<nParameters;j++) {
+
+ artificalExperiments[i][j] = pointsByPercept[j].get(perceptIndices[j]);
+
+ }
+ artificalResults[i] = this.getProposition(context, artificalExperiments[i]);
+
+ test = nextMultiDimCounter(perceptIndices, nbPointsByPercept);
+
+ i++;
+
+ }
+
+
+
+
+ return new Pair<double[][], double[]>(artificalExperiments, artificalResults);
+ }
+
+ private boolean nextMultiDimCounter(int[] indices, int[] bounds){
+
+
+
+ for(int i = 0; i<indices.length;i++) {
+
+ if(indices[i]==bounds[i]-1) {
+ if(i==indices.length-1) {
+ indices[i]=0;
+ return false;
+ }
+ else {
+ indices[i]=0;
+ }
+ }
+ else {
+ indices[i] += 1;
+ return true;
+ }
+
+ }
+
+ return false;
+
+
+ }
+
+ private Pair<double[][], double[]> getRandomlyDistributedArtificialExperiments(int amount){
+
+ double[][] artificalExperiments = new double[amount][nParameters];
+ double[] artificalResults = new double[amount];
+
+
+
+ for (int i = 0; i < amount;i ++) {
+
+ for(int j = 0;j<nParameters;j++) {
+
+ double startRange = this.context.getRanges().get(context.getAmas().getPercepts().get(j)).getStart();
+ double endRange = this.context.getRanges().get(context.getAmas().getPercepts().get(j)).getEnd();
+
+ artificalExperiments[i][j] = startRange + (Math.random()*(endRange - startRange));
+ }
+ artificalResults[i] = this.getProposition(context, artificalExperiments[i]);
+
+ }
+
+ return new Pair<double[][], double[]>(artificalExperiments, artificalResults);
+ }
+
+ @Override
+ public double distance(Experiment experiment) {
+
+ if (coefs[0] == Double.NaN) System.exit(0);
+ double distanceToTheModel = -coefs[0];
+ double normOfOthogonalVectorToThePlane = 0.0;
+
+ for (int i = 1 ; i < coefs.length ; i++) {
+
+ if (Double.isNaN(coefs[i])) coefs[i] = 0.0;
+ distanceToTheModel += -coefs[i] * experiment.getValuesAsArray()[i-1];
+ normOfOthogonalVectorToThePlane += coefs[i]*coefs[i];
+
+ }
+ distanceToTheModel += experiment.getOracleProposition();
+ normOfOthogonalVectorToThePlane += 1;
+
+ distanceToTheModel = Math.abs(distanceToTheModel);
+ normOfOthogonalVectorToThePlane = Math.sqrt(normOfOthogonalVectorToThePlane);
+
+ distanceToTheModel /= normOfOthogonalVectorToThePlane;
+
+ return distanceToTheModel;
+
+ }
+
+ @Override
+ public ArrayList<Experiment> getFirstExperiments() {
+ return firstExperiments;
+ }
+
+ @Override
+ public void setFirstExperiments( ArrayList<Experiment> frstExp) {
+ firstExperiments = frstExp;
+ }
+
+ @Override
+ public String coefsToString() {
+ String coefsString = "";
+ if(coefs != null) {
+ for(int i=0; i<coefs.length; i ++) {
+ coefsString += coefs[i] + "\t";
+ }
+ }
+ return coefsString;
+ }
+
+ @Override
+ public boolean finishedFirstExperiments() {
+ return firstExperiments.size()>= (nParameters + 2);
+ }
+
+ @Override
+ public TypeLocalModel getType() {
+ return TypeLocalModel.MILLER_REGRESSION;
+ }
+}
diff --git a/AMOEBAonAMAK/src/agents/context/localModel/TypeLocalModel.java b/AMOEBAonAMAK/src/agents/context/localModel/TypeLocalModel.java
index 82726f462553a2bb1076c269eff24828316288b0..8d52a78c587b3de8eb38f1a35d03e55199a4bfac 100644
--- a/AMOEBAonAMAK/src/agents/context/localModel/TypeLocalModel.java
+++ b/AMOEBAonAMAK/src/agents/context/localModel/TypeLocalModel.java
@@ -8,10 +8,6 @@ import java.io.Serializable;
*
*/
public enum TypeLocalModel implements Serializable {
- /** The first experiment. */
- FIRST_EXPERIMENT,
- /** The average. */
- AVERAGE,
/** The miller regression. */
MILLER_REGRESSION
}
diff --git a/AMOEBAonAMAK/src/agents/head/ContextPair.java b/AMOEBAonAMAK/src/agents/head/ContextPair.java
new file mode 100644
index 0000000000000000000000000000000000000000..57a6fcee2a7f1e15946639323520fe1de201c227
--- /dev/null
+++ b/AMOEBAonAMAK/src/agents/head/ContextPair.java
@@ -0,0 +1,74 @@
+package agents.head;
+
+import agents.context.Context;
+import agents.percept.Percept;
+
+public class ContextPair<Context1,Context2> {
+
+ private Context l;
+ private Context r;
+ public ContextPair(Context l, Context r){
+ this.l = l;
+ this.r = r;
+ }
+ public Context getL(){ return l; }
+ public Context getR(){ return r; }
+ public void setL(Context l){ this.l = l; }
+ public void setR(Context r){ this.r = r; }
+
+
+ public void print(Percept p) {
+ if(l!=null && r!=null) {
+ //System.out.println("< " + "("+l.getName()+") " +l.getRanges().get(p).getEnd() + " ; " + "("+r.getName()+") " +r.getRanges().get(p).getStart() + " >");
+ }
+ else if(l==null && r==null) {
+ //System.out.println("< " + "-" + " ; " + "-" + " >");
+ }
+ else if(l==null) {
+ //System.out.println("< " + "-" + " ; " + "("+r.getName()+") " +r.getRanges().get(p).getStart() + " >");
+ }
+ else if(r==null) {
+ //System.out.println("< " + "("+l.getName()+") " +l.getRanges().get(p).getEnd() + " ; " + "-" + " >");
+ }
+ else {
+ //System.out.println("ERROR PAIR");
+ }
+
+ }
+
+ public void clear() {
+ this.l = null;
+ this.r = null;
+ }
+
+ public boolean contains(Context ctxt) {
+ return ctxt == this.l || ctxt == this.r;
+ }
+
+ public double rangeToRangeDistance(Percept percept) {
+ return r.getRanges().get(percept).getStart() - l.getRanges().get(percept).getEnd();
+ }
+
+ public boolean containTwoContexts() {
+ return l!=null && r!=null;
+ }
+
+ public double actionProposal(double allowedDifference) {
+ double action = Double.NEGATIVE_INFINITY;
+ double localModelDifference = 0;
+
+ Double[] lLocalModelCoefs = l.getFunction().getCoef();
+ Double[] rLocalModelCoefs = l.getFunction().getCoef();
+
+ if(lLocalModelCoefs.length == rLocalModelCoefs.length) {
+ for(int i = 0;i< lLocalModelCoefs.length; i++) {
+ localModelDifference += Math.abs(lLocalModelCoefs[i] - rLocalModelCoefs[i]);
+ }
+ if(localModelDifference<allowedDifference) {
+ return (l.getActionProposal() + r.getActionProposal())/2;
+ }
+ }
+
+ return action;
+ }
+}
diff --git a/AMOEBAonAMAK/src/agents/head/Criticalities.java b/AMOEBAonAMAK/src/agents/head/Criticalities.java
new file mode 100644
index 0000000000000000000000000000000000000000..900e01832d9df06b8c4f12f222047b201edfe510
--- /dev/null
+++ b/AMOEBAonAMAK/src/agents/head/Criticalities.java
@@ -0,0 +1,76 @@
+package agents.head;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+
+public class Criticalities implements Cloneable{
+
+ HashMap<String, Double> currentValues;
+
+ HashMap<String, Double> currentMeanValues;
+
+ HashMap<String, ArrayList<Double>> lastValues;
+
+ int temporalWindowSize;
+
+
+
+ public Criticalities(int temporalWindowSizeValue) {
+
+ temporalWindowSize = temporalWindowSizeValue;
+ currentValues = new HashMap<String, Double>();
+ currentMeanValues = new HashMap<String, Double>();
+ lastValues = new HashMap<String, ArrayList<Double>>();
+
+
+ }
+
+
+
+ public void addCriticality(String name, double value) {
+ currentValues.put(name, value);
+
+ if(lastValues.get(name)==null) {
+ lastValues.put(name, new ArrayList<Double>());
+ }
+ lastValues.get(name).add(value);
+
+
+ if (lastValues.get(name).size() >= temporalWindowSize) {
+ lastValues.get(name).remove(0);
+ }
+ }
+
+ public double getCriticality(String name) {
+ return currentValues.get(name);
+ }
+
+ public Double getCriticalityMean(String name) {
+ return currentMeanValues.get(name);
+ }
+
+ public void updateMeans() {
+
+ for(String criticalityName : currentValues.keySet()) {
+
+ double valuesSum = 0.0;
+ for (Double d : lastValues.get(criticalityName)) {
+ valuesSum += d;
+ }
+
+ currentMeanValues.put(criticalityName,valuesSum / lastValues.get(criticalityName).size());
+
+
+
+ }
+
+
+ }
+
+ public HashMap<String, ArrayList<Double>> getLastValues() {
+
+ return lastValues;
+
+ }
+
+}
diff --git a/AMOEBAonAMAK/src/agents/head/DynamicPerformance.java b/AMOEBAonAMAK/src/agents/head/DynamicPerformance.java
new file mode 100644
index 0000000000000000000000000000000000000000..4c0652297e33f9e77ea424b41ecaa11d5c53ffa3
--- /dev/null
+++ b/AMOEBAonAMAK/src/agents/head/DynamicPerformance.java
@@ -0,0 +1,66 @@
+package agents.head;
+
+import java.io.Serializable;
+
+public class DynamicPerformance implements Serializable{
+ private static final long serialVersionUID = 1L;
+
+ public int successesBeforeDiminution;
+ public int conflictsBeforeAugmentation;
+ public Double performanceIndicator;
+ public int performanceCounter;
+
+ public double augmentationFactor;
+ public double diminutionFactor;
+
+ public Double minPerformanceIndicator;
+
+ // Required for serialization by XML
+ public DynamicPerformance() {};
+
+ public DynamicPerformance(int nbSuccessesBeforeDiminution, int nbConflictsBeforeAugmentation,
+ double performanceIndicatorValue, double augmentationFactorValue, double diminutionFactorValue,
+ double minPerformanceIndicatorValue) {
+
+ successesBeforeDiminution = nbSuccessesBeforeDiminution;
+ conflictsBeforeAugmentation = nbConflictsBeforeAugmentation;
+ performanceIndicator = performanceIndicatorValue;
+ performanceCounter = 0;
+
+ augmentationFactor = augmentationFactorValue;
+ diminutionFactor = diminutionFactorValue;
+
+ minPerformanceIndicator = minPerformanceIndicatorValue;
+
+ }
+
+ public void update(double currentCriticalityMean) {
+
+ if (currentCriticalityMean > performanceIndicator) {
+ performanceCounter--;
+ } else {
+ performanceCounter++;
+ }
+
+ if (performanceCounter <= conflictsBeforeAugmentation * (-1)) {
+ performanceCounter = 0;
+ performanceIndicator += augmentationFactor * performanceIndicator;
+ }
+
+ if (performanceCounter >= successesBeforeDiminution) {
+ performanceCounter = 0;
+ performanceIndicator -= diminutionFactor * performanceIndicator;
+ performanceIndicator = Math.max(minPerformanceIndicator, performanceIndicator);
+ }
+
+ }
+
+ public void setPerformanceIndicator(double value) {
+ performanceIndicator = value;
+ }
+
+ public double getPerformanceIndicator() {
+ return performanceIndicator;
+ }
+
+}
diff --git a/AMOEBAonAMAK/src/agents/head/EndogenousRequest.java b/AMOEBAonAMAK/src/agents/head/EndogenousRequest.java
new file mode 100644
index 0000000000000000000000000000000000000000..e6c7ea98015042a6cc07c5e84d199b729cb16343
--- /dev/null
+++ b/AMOEBAonAMAK/src/agents/head/EndogenousRequest.java
@@ -0,0 +1,102 @@
+package agents.head;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.HashMap;
+import java.util.Iterator;
+
+import org.junit.platform.commons.util.ToStringBuilder;
+
+import agents.context.Context;
+import agents.percept.Percept;
+import utils.Pair;
+
+public class EndogenousRequest {
+
+
+ private Integer priority;
+ private HashMap<Percept, Double> request;
+ private HashMap<Percept, Pair<Double, Double>> bounds;
+ private ArrayList<Context> askingContexts;
+ private String name;
+ private REQUEST requestType;
+
+ public EndogenousRequest(HashMap<Percept, Double> rqst, HashMap<Percept, Pair<Double, Double>> bnds, int prty, ArrayList<Context> contexts, REQUEST type) {
+
+ request = rqst;
+ bounds = bnds;
+ priority = prty;
+ askingContexts = contexts;
+
+ name = "";
+
+ for(Context ctxt: askingContexts) {
+ name += ctxt.getName();
+ }
+
+ requestType = type;
+ }
+
+ public EndogenousRequest(HashMap<Percept, Double> rqst, Integer prty) {
+
+ request = rqst;
+ priority = prty;
+ }
+
+ public Integer getPriority() {
+ return priority;
+ }
+
+ public HashMap<Percept, Double> getRequest(){
+ return request;
+ }
+
+ public String toString() {
+ String m="ASK BY ";
+ for(Context ctxt : askingContexts) {
+ m+= ctxt.getName() + " ";
+ }
+ m+=priority + " ";
+ m+= request + " ";
+ m+= requestType;
+ return m;
+ }
+
+ public ArrayList<Context> getAskingContexts(){
+ return askingContexts;
+ }
+
+ public String getName() {
+ return name;
+ }
+
+ public boolean testIfContextsAlreadyAsked(ArrayList<Context> contexts) {
+ boolean test = true;
+ for(Context ctxt : contexts) {
+ test = test && askingContexts.contains(ctxt);
+ }
+ return test;
+ }
+
+ public boolean requestInBounds(HashMap<Percept, Double> rqt) {
+ boolean test = true;
+
+
+ Iterator<Percept> it = rqt.keySet().iterator();
+
+ while(test && it.hasNext()) {
+ Percept pct = (Percept) it.next();
+ test = test && ( (bounds.get(pct).getA() < rqt.get(pct)) && (rqt.get(pct) < bounds.get(pct).getB() ));
+ }
+
+
+ return test;
+ }
+
+ public REQUEST getType() {
+ return requestType;
+ }
+
+
+
+}
diff --git a/AMOEBAonAMAK/src/agents/head/Head.java b/AMOEBAonAMAK/src/agents/head/Head.java
index 86ac00265a6e04b1f5e1b34c25a4adaa6edfefe1..261df1a11146fb554e063c0d72abb80bddd11757 100644
--- a/AMOEBAonAMAK/src/agents/head/Head.java
+++ b/AMOEBAonAMAK/src/agents/head/Head.java
@@ -1,63 +1,72 @@
package agents.head;
import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.Comparator;
import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.PriorityQueue;
+import java.util.Queue;
import agents.AmoebaAgent;
import agents.context.Context;
+import agents.context.CustomComparator;
import agents.percept.Percept;
import kernel.AMOEBA;
import ncs.NCS;
+import utils.Pair;
+import utils.PrintOnce;
+import utils.RandomUtils;
+import utils.TRACE_LEVEL;
/**
* The Class Head.
*/
public class Head extends AmoebaAgent {
+
+ // MEMBERS ---------------------
+
private Context bestContext;
private Context lastUsedContext;
private Context newContext;
- private HashMap<Percept, Double> currentSituation = new HashMap<>();
- private ArrayList<Context> activatedContexts = new ArrayList<>();
- private ArrayList<Double> xLastCriticityValues = new ArrayList<>();
- private int numberOfCriticityValuesForAverage = 100;
+ HashMap<Percept, Double> currentSituation = new HashMap<Percept, Double>();
- private int nConflictBeforeAugmentation = 1;
- private int nSuccessBeforeDiminution = 50;
- private int perfIndicator = 1;
- private int nConflictBeforeInexactAugmentation = 2;
- private int nSuccessBeforeInexactDiminution = 50;
- private int perfIndicatorInexact = 0;
+ public Criticalities criticalities;
+ public Criticalities endogenousCriticalities;
- private double prediction;
- private double oracleValue;
- private double criticity;
- private double averagePredictionCriticity;
+ private ArrayList<Context> activatedContexts = new ArrayList<Context>();
+ private ArrayList<Context> activatedNeighborsContexts = new ArrayList<Context>();
- private double errorAllowed = 1.0;
- private double augmentationFactorError = 1.05;
- private double diminutionFactorError = 0.9;
- private double minErrorAllowed = 1.00;
- private double inexactAllowed = 0.4;
- private double augmentationInexactError = 1.8;
- private double diminutionInexactError = 0.6;
- private double minInexactAllowed = 0.5;
+ Queue<EndogenousRequest> endogenousRequests = new PriorityQueue<EndogenousRequest>(new Comparator<EndogenousRequest>(){
+ public int compare(EndogenousRequest r1, EndogenousRequest r2) {
+ return r2.getPriority().compareTo(r1.getPriority());
+ }
+ });
+
+ static double lembda = 0.99;
+ // -----------------------------
+
+ public void setDataForErrorMargin(double errorAllowed, double augmentationFactorError, double diminutionFactorError,
+ double minErrorAllowed, int nConflictBeforeAugmentation, int nSuccessBeforeDiminution) {
- private boolean noCreation = true;
- private boolean useOracle = true;
- private boolean firstContext = false;
- private boolean contextFromPropositionWasSelected = false;
+ getAmas().data.predictionPerformance = new DynamicPerformance(nSuccessBeforeDiminution, nConflictBeforeAugmentation,
+ errorAllowed, augmentationFactorError, diminutionFactorError, minErrorAllowed);
- /**
- * Instantiates a new head.
- * @param the amoeba which the head is attached to.
- */
- public Head(AMOEBA amas) {
- super(amas);
+ getAmas().data.regressionPerformance = new DynamicPerformance(100, 100, 200, 0.5, 0.5, 1);
+
+ getAmas().data.mappingPerformance = new DynamicPerformance(100000, 1000000, getEnvironment().getMappingErrorAllowed(), 1.1,
+ 0.9, 1);
}
- public void proposition(Context c) {
- activatedContexts.add(c);
+ public Head(AMOEBA amoeba) {
+ super(amoeba);
+
+ for(int i =0 ; i< 20;i++) {
+ getAmas().data.executionTimesSums[i]=0.0;
+ }
}
/**
@@ -65,446 +74,1193 @@ public class Head extends AmoebaAgent {
* from context agents when needed.
*/
@Override
- protected void onAct() {
- for (Percept pct : this.amas.getPercepts()) {
+ public void onAct() {
+
+ getAmas().data.currentCriticalityPrediction = 0;
+ getAmas().data.currentCriticalityMapping = 0;
+ getAmas().data.currentCriticalityConfidence = 0;
+
+ for (Percept pct : getAmas().getPercepts()) {
currentSituation.put(pct, pct.getValue());
}
- activatedContexts.size();
+ getAmas().data.nPropositionsReceived = activatedContexts.size();
+ getAmas().data.newContextWasCreated = false;
setContextFromPropositionWasSelected(false);
- oracleValue = this.amas.getPerceptions("oracle");
+ getAmas().data.oldOracleValue = getAmas().data.oracleValue;
+ getAmas().data.oracleValue = getAmas().getPerceptions("oracle");
+ setAverageRegressionPerformanceIndicator();
/* The head memorize last used context agent */
lastUsedContext = bestContext;
bestContext = null;
- /* useOracle means that data are labeled */
- if (useOracle) {
+ if (getAmas().data.useOracle) {
playWithOracle();
} else {
playWithoutOracle();
}
- updateStatisticalInformations();
+ updateStatisticalInformations(); /// regarder dans le détail, possible que ce pas trop utile
newContext = null;
+
}
- /**
- * Play and use the oracle, allowing for learning.
- */
private void playWithOracle() {
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("\n\n")));
+ getAmas().data.executionTimes[0]=System.currentTimeMillis();
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("------------------------------------------------------------------------------------"
+ + "---------------------------------------- PLAY WITH ORACLE")));
+
if (activatedContexts.size() > 0) {
- selectBestContext(); // using highest confidence
+ //selectBestContext(); // using highest confidence
+ selectBestContextWithDistanceToModel(); // using closest distance
+ // selectBestContextWithDistanceToModel();
+ } else {
+ bestContext = lastUsedContext;
}
if (bestContext != null) {
setContextFromPropositionWasSelected(true);
- prediction = bestContext.getActionProposal();
+ getAmas().data.prediction = bestContext.getActionProposal();
- } else if (!noCreation) { /*
- * noCreation is only used to disable creation of contexts, for research
- * purposes
- */
- getNearestContextAsBestContext();
+ } else { // happens only at the beginning
+ setNearestContextAsBestContext();
}
/* Compute the criticity. Will be used by context agents. */
- criticity = Math.abs(oracleValue - prediction);
+ getAmas().data.criticity = Math.abs(getAmas().data.oracleValue - getAmas().data.prediction);
+
+
+ /* If we have a bestcontext, send a selection message to it */
+ if (bestContext != null) {
+ bestContext.notifySelection();
+ getEnvironment().trace(TRACE_LEVEL.STATE, new ArrayList<String>(Arrays.asList(bestContext.getName(),
+ "*********************************************************************************************************** BEST CONTEXT")));
+ }
- selfAnalysationOfContexts();
+ getAmas().data.executionTimes[0]=System.currentTimeMillis()- getAmas().data.executionTimes[0];
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("bestContext != null 1", "" + (bestContext != null))));
+ getAmas().data.executionTimes[1]=System.currentTimeMillis();
+ // endogenousPlay();
+ getAmas().data.executionTimes[1]=System.currentTimeMillis()- getAmas().data.executionTimes[1];
+
+ getAmas().data.executionTimes[2]=System.currentTimeMillis();
+ selfAnalysationOfContexts4();
+ getAmas().data.executionTimes[2]=System.currentTimeMillis()- getAmas().data.executionTimes[2];
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("bestContext != null 2", "" + (bestContext != null))));
+
+ getAmas().data.executionTimes[3]=System.currentTimeMillis();
NCSDetection_IncompetentHead(); /*
- * If there isn't any proposition or only bad propositions, the head is
- * incompetent. It needs help from a context.
- */
+ * If there isn't any proposition or only bad propositions, the head is
+ * incompetent. It needs help from a context.
+ */
+ getAmas().data.executionTimes[3]=System.currentTimeMillis()- getAmas().data.executionTimes[3];
+
+
+ getAmas().data.executionTimes[4]=System.currentTimeMillis();
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("bestContext != null 3", "" + (bestContext != null))));
NCSDetection_Concurrence(); /* If result is good, shrink redundant context (concurrence NCS) */
+ getAmas().data.executionTimes[4]=System.currentTimeMillis()- getAmas().data.executionTimes[4];
+
+ getAmas().data.executionTimes[5]=System.currentTimeMillis();
NCSDetection_Create_New_Context(); /* Finally, head agent check the need for a new context agent */
- }
+ getAmas().data.executionTimes[5]=System.currentTimeMillis()- getAmas().data.executionTimes[5];
+
+ getAmas().data.executionTimes[6]=System.currentTimeMillis();
+ NCSDetection_Context_Overmapping();
+ getAmas().data.executionTimes[6]=System.currentTimeMillis()- getAmas().data.executionTimes[6];
+
+
+
+ getAmas().data.executionTimes[11]=System.currentTimeMillis();
+ NCSDetection_ChildContext();
+ getAmas().data.executionTimes[11]=System.currentTimeMillis()- getAmas().data.executionTimes[11];
+
+ getAmas().data.executionTimes[12]=System.currentTimeMillis();
+ NCSDetection_PotentialRequest();
+ getAmas().data.executionTimes[12]=System.currentTimeMillis()- getAmas().data.executionTimes[12];
+
+
+
+ getAmas().data.executionTimes[7]=System.currentTimeMillis();
+
+ criticalities.addCriticality("spatialCriticality",
+ (getMinMaxVolume() - getVolumeOfAllContexts()) / getMinMaxVolume());
+
+ getAmas().data.spatialGeneralizationScore = getVolumeOfAllContexts() / getAmas().getContexts().size();
+
+ double globalConfidence = 0;
+
+ for (Context ctxt : getAmas().getContexts()) {
+ globalConfidence += ctxt.getConfidence();
+ }
+ globalConfidence = globalConfidence / getAmas().getContexts().size();
- /**
- * Play without oracle, no learning.
- */
- private void playWithoutOracle() {
+ if (activatedNeighborsContexts.size() > 1) {
- selectBestContext();
- if (bestContext != this.lastUsedContext) {
- prediction = bestContext.getActionProposal();
- } else {
- ArrayList<Context> allContexts = amas.getContexts();
- Context nearestContext = this.getNearestContext(allContexts);
- prediction = nearestContext.getActionProposal();
- bestContext = nearestContext;
- }
- bestContext.getFunction().getFormula(bestContext);
- criticity = Math.abs(oracleValue - prediction);
- }
- private void NCSDetection_Create_New_Context() {
- /* Finally, head agent check the need for a new context agent */
- boolean newContextCreated = false;
- ArrayList<Context> allContexts = amas.getContexts();
- if (getDistanceToNearestGoodContext(allContexts) > 0) {
- Context context = createNewContext();
+ int i = 1;
+ for (Context ctxt : activatedNeighborsContexts) {
- bestContext = context;
- newContext = context;
- newContextCreated = true;
- }
+ for (Context otherCtxt : activatedNeighborsContexts.subList(i, activatedNeighborsContexts.size())) {
- if (!newContextCreated) {
- updateStatisticalInformations();
- }
- }
+ // if(nearestLocalNeighbor(ctxt, otherCtxt)) {
+
+ Pair<Double, Percept> distanceAndPercept = ctxt.distance(otherCtxt);
+ // distanceAndPercept.getB());
+ if (distanceAndPercept.getA() < 0) {
+ criticalities.addCriticality("localOverlapMappingCriticality",
+ Math.abs(distanceAndPercept.getA()));
+ } else if (distanceAndPercept.getA() > 0 && distanceAndPercept.getB() != null) {
+ criticalities.addCriticality("localVoidMappingCriticality", distanceAndPercept.getA());
+ } else {
+ criticalities.addCriticality("localOpenVoidMappingCriticality", distanceAndPercept.getA());
+ }
+
+ // }
- private void NCSDetection_Concurrence() {
- /* If result is good, shrink redundant context (concurrence NCS) */
- if (bestContext != null && criticity <= this.errorAllowed) {
- for (int i = 0; i < activatedContexts.size(); i++) {
- if (activatedContexts.get(i) != bestContext && !activatedContexts.get(i).isDying()
- && this.getCriticity(activatedContexts.get(i)) <= this.errorAllowed) {
- activatedContexts.get(i).solveNCS_Concurrence(this);
}
+ i++;
+
}
+
}
+
+ getAmas().data.mappingPerformance.setPerformanceIndicator(getEnvironment().getMappingErrorAllowed());// Math.pow(world.getMappingErrorAllowed(),
+ // world.getScheduler().getPercepts().size());
+
+ getAmas().data.evolutionCriticalityPrediction = (lembda * getAmas().data.evolutionCriticalityPrediction)
+ + ((1 - lembda) * getAmas().data.currentCriticalityPrediction);
+ getAmas().data.evolutionCriticalityMapping = (lembda * getAmas().data.evolutionCriticalityMapping)
+ + ((1 - lembda) * getAmas().data.currentCriticalityMapping);
+ getAmas().data.evolutionCriticalityConfidence = (lembda * getAmas().data.evolutionCriticalityConfidence)
+ + ((1 - lembda) * getAmas().data.currentCriticalityConfidence);
+
+
+ getAmas().data.executionTimes[7]=System.currentTimeMillis()- getAmas().data.executionTimes[7];
+
+ for(int i = 0 ; i<20;i++) {
+ getAmas().data.executionTimesSums[i] += getAmas().data.executionTimes[i];
+ }
+
+
+
}
- private void NCSDetection_IncompetentHead() {
- /*
- * If there isn't any proposition or only bad propositions, the head is
- * incompetent. It needs help from a context.
- */
- if (activatedContexts.isEmpty() || (criticity > this.errorAllowed && !oneOfProposedContextWasGood())) {
- ArrayList<Context> allContexts = amas.getContexts();
-
- Context c = getNearestGoodContext(allContexts);
- if (c != null)
- c.solveNCS_IncompetentHead(this);
- ;
- bestContext = c;
-
- /* This allow to test for all contexts rather than the nearest */
- /*
- * for (Agent a : allContexts) { Context c = (Context) a; if
- * (Math.abs((c.getActionProposal() - oracleValue)) <= errorAllowed && c !=
- * newContext && !c.isDying() && c != bestContext && !contexts.contains(c)) {
- * c.growRanges(this);
- *
- * } }
- */
-
+ public double getMinMaxVolume() {
+ double minMaxVolume = 1;
+ for (Percept pct : getAmas().getPercepts()) {
+ minMaxVolume *= pct.getMinMaxDistance();
}
+ return (minMaxVolume == 0.0) ? 1 : minMaxVolume;
}
- private void selfAnalysationOfContexts() {
- /* All context which proposed itself must analyze its proposition */
- for (int i = 0; i < activatedContexts.size(); i++) {
- if (activatedContexts.get(i).isDying()) {
- activatedContexts.remove(i);
- } else
- activatedContexts.get(i).analyzeResults(this);
+ public double getVolumeOfAllContexts() {
+ double allContextsVolume = 0;
+ for (Context ctxt : getAmas().getContexts()) {
+ allContextsVolume += ctxt.getVolume();
}
+ return allContextsVolume;
+ }
+
+ public double getSpatialCriticality() {
+ return criticalities.getCriticality("spatialCriticality");
}
/**
- * One of proposed context was good.
- *
- * @return true, if successful
+ * Play without oracle.
*/
- private boolean oneOfProposedContextWasGood() {
- boolean b = false;
- for (Context c : activatedContexts) {
- if (oracleValue - c.getActionProposal() < errorAllowed) {
- b = true;
+ private void playWithoutOracle() {
+
+ logger().debug("HEAD without oracle", "Nombre de contextes activés: " + activatedContexts.size());
+
+ selectBestContext();
+ if (bestContext != null) {
+ getAmas().data.noBestContext = false;
+ getAmas().data.prediction = bestContext.getActionProposal();
+ } else {
+
+ getAmas().data.noBestContext = true;
+ Context nearestContext = this.getNearestContext(activatedNeighborsContexts);
+ if(nearestContext != null) {
+ getAmas().data.prediction = nearestContext.getActionProposal();
+ bestContext = nearestContext;
+ } else {
+ //TODO THIS IS VERY INEFICIENT ! amoeba should not look globally, but right now there's no other strategy.
+ // To limit performance impact, we limit our search on a random sample.
+ // A better way would be to increase neighborhood.
+ PrintOnce.print("Play without oracle : no nearest context in neighbors, searching in a random sample. (only shown once)");
+ List<Context> searchList = RandomUtils.pickNRandomElements(getAmas().getContexts(), 100);
+ nearestContext = this.getNearestContext(searchList);
+ if(nearestContext != null) {
+ getAmas().data.prediction = nearestContext.getActionProposal();
+ } else {
+ getAmas().data.prediction = 0.0;
+ }
}
}
+ if(bestContext != null) {
+ logger().debug("HEAD without oracle", "Best context selected without oracle is : " + bestContext.getName());
+ // Config.print("With function : " +
+ // bestContext.getFunction().getFormula(bestContext), 0);
+ logger().debug("HEAD without oracle",
+ "BestContext : " + bestContext.toStringFull() + " " + bestContext.getConfidence());
+ // functionSelected = bestContext.getFunction().getFormula(bestContext);
+
+ }
+ else {
+ logger().debug("HEAD without oracle", "no Best context selected ");
+ }
+
+ getAmas().data.criticity = Math.abs(getAmas().data.oracleValue - getAmas().data.prediction);
- return b;
-
+ endogenousPlay();
}
- /**
- * Creates the new context.
- *
- * @return the context
- */
- private Context createNewContext() {
- amas.getEnvironment().raiseNCS(NCS.CREATE_NEW_CONTEXT);
- Context context;
- if (firstContext) {
- context = new Context(amas, this);
+ private void endogenousPlay() {
+
+ getAmas().data.endogenousPredictionActivatedContextsOverlaps = null;
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluence = null;
+
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidence = null;
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidence = null;
+
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolume = null;
+
+ getAmas().data.endogenousPredictionActivatedContextsSharedIncompetence = null;
+ getAmas().data.endogenousPredictionNContextsByInfluence = null;
+
+ if (uniqueActivatedContext()) {
+ getAmas().data.endogenousPredictionActivatedContextsOverlaps = activatedContexts.get(0).getActionProposal();
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluence = activatedContexts.get(0)
+ .getActionProposal();
+ getAmas().data.endogenousPredictionActivatedContextsSharedIncompetence = activatedContexts.get(0).getActionProposal();
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidence = activatedContexts.get(0)
+ .getActionProposal();
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidence = activatedContexts.get(0)
+ .getActionProposal();
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolume = activatedContexts.get(0)
+ .getActionProposal();
+ getAmas().saver.newManualSave("Unique Context");
+ } else if (severalActivatedContexts()) {
+ NCS_EndogenousCompetition();
} else {
- context = new Context(amas, this);
- firstContext = true;
+ if (surroundingContexts()) {
+ NCS_EndogenousSharedIncompetence();
+ } else if (activatedContexts.size() > 0) {
+ getAmas().saver.newManualSave("Other activated");
+ } else if (activatedContexts.size() == 0) {
+ getAmas().saver.newManualSave("Other non activated");
+ }
+// else if(noActivatedContext()) {
+// endogenousPrediction = -2000.0;
+// NCS_EndogenousIncompetence();
+// }
+// else {
+// endogenousPrediction = -3000.0;
+// }
+// else {
+// endogenousPrediction = prediction;
+// }
}
- return context;
- }
+ // Endogenous prediction N contexts //
- /**
- * Update statistical informations.
- */
- private void updateStatisticalInformations() {
- xLastCriticityValues.add(criticity);
+ Double endogenousSumTerm = 0.0;
+ Double endogenousNormalizationTerm = 0.0;
- averagePredictionCriticity = 0;
- for (Double d : xLastCriticityValues) {
- averagePredictionCriticity += d;
+ for (Context ctxt : activatedNeighborsContexts) {
+ endogenousSumTerm += ctxt.getInfluenceWithConfidence(currentSituation) * ctxt.getActionProposal();
+ endogenousNormalizationTerm += ctxt.getInfluenceWithConfidence(currentSituation);
}
- averagePredictionCriticity /= xLastCriticityValues.size();
+ getAmas().data.endogenousPredictionNContexts = endogenousSumTerm / endogenousNormalizationTerm;
+
+ // Endogenous prediction N contexts by influence //
+
+ getAmas().data.maxConfidence = Double.NEGATIVE_INFINITY;
+ getAmas().data.minConfidence = Double.POSITIVE_INFINITY;
+
+ ArrayList<Context> contextsNeighborsByInfluence = new ArrayList<>();
+ for (Context ctxt : getAmas().getContexts()) {
+
+ if (ctxt.getConfidence() > getAmas().data.maxConfidence) {
+ getAmas().data.maxConfidence = ctxt.getConfidence();
+ }
+ if (ctxt.getConfidence() < getAmas().data.minConfidence) {
+ getAmas().data.minConfidence = ctxt.getConfidence();
+ }
+
+ if (ctxt.getInfluenceWithConfidence(currentSituation) > 0.5) {
+ contextsNeighborsByInfluence.add(ctxt);
- if (xLastCriticityValues.size() >= numberOfCriticityValuesForAverage) {
- xLastCriticityValues.remove(0);
+ }
}
- if (averagePredictionCriticity > errorAllowed) {
- perfIndicator--;
- } else {
- perfIndicator++;
+ endogenousSumTerm = 0.0;
+ endogenousNormalizationTerm = 0.0;
+ if (contextsNeighborsByInfluence.size() > 0) {
+ for (Context ctxt : contextsNeighborsByInfluence) {
+ endogenousSumTerm += ctxt.getInfluenceWithConfidence(currentSituation) * ctxt.getActionProposal();
+ endogenousNormalizationTerm += ctxt.getInfluenceWithConfidence(currentSituation);
+ }
+
+ getAmas().data.endogenousPredictionNContextsByInfluence = endogenousSumTerm / endogenousNormalizationTerm;
}
- if (perfIndicator <= nConflictBeforeAugmentation * (-1)) {
- perfIndicator = 0;
- errorAllowed *= augmentationFactorError;
+ if (getAmas().data.endogenousPredictionActivatedContextsOverlaps == null) {
+ getAmas().data.endogenousPredictionActivatedContextsOverlaps = getAmas().data.prediction;
}
- if (perfIndicator >= nSuccessBeforeDiminution) {
- perfIndicator = 0;
- errorAllowed *= diminutionFactorError;
- errorAllowed = Math.max(minErrorAllowed, errorAllowed);
+ if (getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluence == null) {
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluence = getAmas().data.prediction;
}
- if (averagePredictionCriticity > inexactAllowed) {
- perfIndicatorInexact--;
- } else {
- perfIndicatorInexact++;
+ if (getAmas().data.endogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidence == null) {
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidence = getAmas().data.prediction;
}
- if (perfIndicatorInexact <= nConflictBeforeInexactAugmentation * (-1)) {
- perfIndicatorInexact = 0;
- inexactAllowed *= augmentationInexactError;
+ if (getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidence == null) {
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidence = getAmas().data.prediction;
}
- if (perfIndicatorInexact >= nSuccessBeforeInexactDiminution) {
- perfIndicatorInexact = 0;
- inexactAllowed *= diminutionInexactError;
- inexactAllowed = Math.max(minInexactAllowed, inexactAllowed);
+ if (getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolume == null) {
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolume = getAmas().data.prediction;
}
- }
- /**
- * Select best context.
- */
- private void selectBestContext() {
- Context bc;
- if (activatedContexts.isEmpty()) {
- bc = lastUsedContext;
- } else {
- bc = activatedContexts.get(0);
+ if (getAmas().data.endogenousPredictionActivatedContextsSharedIncompetence == null) {
+ getAmas().data.endogenousPredictionActivatedContextsSharedIncompetence = getAmas().data.prediction;
}
- double currentConfidence = Double.NEGATIVE_INFINITY;
- for (Context context : activatedContexts) {
- if (context.getConfidence() > currentConfidence) {
- bc = context;
- currentConfidence = bc.getConfidence();
- }
+ if (getAmas().data.endogenousPredictionNContextsByInfluence == null) {
+ getAmas().data.endogenousPredictionNContextsByInfluence = getAmas().data.prediction;
}
- bestContext = bc;
}
- /**
- * Change oracle connection.
- */
- public void changeOracleConnection() {
- useOracle = !useOracle;
+ private boolean noActivatedContext() {
+ // Test if only one context is activated
+ return activatedContexts.size() == 0;
}
- /**
- * Checks if is context from proposition was selected.
- *
- * @return true, if is context from proposition was selected
- */
- public boolean isContextFromPropositionWasSelected() {
- return contextFromPropositionWasSelected;
+ public boolean uniqueActivatedContext() {
+ // Test if only one context is activated
+ return activatedContexts.size() == 1;
}
- public Head clone() throws CloneNotSupportedException {
- return (Head) super.clone();
+ public boolean severalActivatedContexts() {
+ // Test if several context are activated
+ return activatedContexts.size() > 1;
}
- public void clearAllUseableContextLists() {
- activatedContexts.clear();
- }
-
-
- /**
- * Sets the data for error margin.
- *
- * @param errorAllowed the error allowed
- * @param augmentationFactorError the augmentation factor error
- * @param diminutionFactorError the diminution factor error
- * @param minErrorAllowed the min error allowed
- * @param nConflictBeforeAugmentation the n conflict before augmentation
- * @param nSuccessBeforeDiminution the n success before diminution
- */
- public void setDataForErrorMargin(double errorAllowed, double augmentationFactorError, double diminutionFactorError,
- double minErrorAllowed, int nConflictBeforeAugmentation, int nSuccessBeforeDiminution) {
- this.errorAllowed = errorAllowed;
- this.augmentationFactorError = augmentationFactorError;
- this.diminutionFactorError = diminutionFactorError;
- this.minErrorAllowed = minErrorAllowed;
- this.nConflictBeforeAugmentation = nConflictBeforeAugmentation;
- this.nSuccessBeforeDiminution = nSuccessBeforeDiminution;
- }
+ public boolean surroundingContexts() {
+ // Test if there are surrounding contexts
+ boolean testSurroudingContext = false;
- /**
- * Sets the data for inexact margin.
- *
- * @param inexactAllowed the inexact allowed
- * @param augmentationInexactError the augmentation inexact error
- * @param diminutionInexactError the diminution inexact error
- * @param minInexactAllowed the min inexact allowed
- * @param nConflictBeforeInexactAugmentation the n conflict before inexact
- * augmentation
- * @param nSuccessBeforeInexactDiminution the n success before inexact
- * diminution
- */
- public void setDataForInexactMargin(double inexactAllowed, double augmentationInexactError,
- double diminutionInexactError, double minInexactAllowed, int nConflictBeforeInexactAugmentation,
- int nSuccessBeforeInexactDiminution) {
- this.inexactAllowed = inexactAllowed;
- this.augmentationInexactError = augmentationInexactError;
- this.diminutionInexactError = diminutionInexactError;
- this.minInexactAllowed = minInexactAllowed;
- this.nConflictBeforeInexactAugmentation = nConflictBeforeInexactAugmentation;
- this.nSuccessBeforeInexactDiminution = nSuccessBeforeInexactDiminution;
- }
+ HashMap<Percept, ContextPair<Context, Context>> sharedIncompetenceContextPairs = getSharedIncompetenceContextPair();
- /**
- * Sets the no creation.
- *
- * @param noCreation the new no creation
- */
- public void setNoCreation(boolean noCreation) {
- this.noCreation = noCreation;
- }
+ // displayContexts();
- /**
- * Sets the new context.
- *
- * @param newContext the new new context
- */
- public void setNewContext(Context newContext) {
- this.newContext = newContext;
+ for (Percept pcpt : getAmas().getPercepts()) {
+
+ if (sharedIncompetenceContextPairs.get(pcpt) != null) {
+ if (sharedIncompetenceContextPairs.get(pcpt).containTwoContexts()) {
+ testSurroudingContext = true;
+ break;
+ }
+ }
+
+ }
+
+ return testSurroudingContext;
}
- /**
- * Sets the context from proposition was selected.
- *
- * @param contextFromPropositionWasSelected the new context from proposition was
- * selected
- */
- public void setContextFromPropositionWasSelected(boolean contextFromPropositionWasSelected) {
- this.contextFromPropositionWasSelected = contextFromPropositionWasSelected;
+ private HashMap<Percept, ContextPair<Context, Context>> getSharedIncompetenceContextPair() {
+ HashMap<Percept, ContextPair<Context, Context>> sharedIncompetenceContextPairs = new HashMap<>();
+
+ for (Percept pct : getAmas().getPercepts()) {
+ ContextPair<Context, Context> nearestContexts = computeNearestContextsByPercept(pct);
+ if (nearestContexts.getL() != null && nearestContexts.getR() != null) {
+ sharedIncompetenceContextPairs.put(pct, nearestContexts);
+ }
+ }
+
+ return sharedIncompetenceContextPairs;
}
-
- private void getNearestContextAsBestContext() {
- ArrayList<Context> allContexts = amas.getContexts();
- Context nearestContext = this.getNearestContext(allContexts);
+ private ContextPair<Context, Context> computeNearestContextsByPercept(Percept pct) {
+ ContextPair<Context, Context> nearestContexts = new ContextPair<>(null, null);
+ boolean startNeighbor = false;
+ boolean endNeighbor = false;
- if (nearestContext != null) {
- prediction = nearestContext.getActionProposal();
- } else {
- prediction = 0;
- }
+ ArrayList<Context> activatedContextInOtherPercepts = getAllActivatedContextsExeptForOnePercept(pct);
+ if (activatedContextInOtherPercepts.size() > 0) {
- bestContext = nearestContext;
- }
+ CustomComparator rangeStartComparator = new CustomComparator(pct, "start");
+ Collections.sort(activatedContextInOtherPercepts, rangeStartComparator);
- /**
- * Gets the nearest good context.
- *
- * @param allContext the all context
- * @return the nearest good context
- */
- private Context getNearestGoodContext(ArrayList<Context> allContext) {
- Context nearest = null;
- for (AmoebaAgent a : allContext) {
- Context c = (Context) a;
- if (Math.abs((c.getActionProposal() - oracleValue)) <= errorAllowed && c != newContext && !c.isDying()) {
- if (nearest == null || getExternalDistanceToContext(c) < getExternalDistanceToContext(nearest)) {
- nearest = c;
+ for (Context ctxt : activatedContextInOtherPercepts) {
+ if (ctxt.getRanges().get(pct).getRange("start") > pct.getValue() && !startNeighbor) {
+ nearestContexts.setR(ctxt);
+ startNeighbor = true;
}
}
+
+ CustomComparator rangeEndComparator = new CustomComparator(pct, "end");
+ Collections.sort(activatedContextInOtherPercepts, rangeEndComparator);
+ Collections.reverse(activatedContextInOtherPercepts);
+
+ for (Context ctxt : activatedContextInOtherPercepts) {
+ if (ctxt.getRanges().get(pct).getRange("end") < pct.getValue() && !endNeighbor) {
+ nearestContexts.setL(ctxt);
+ endNeighbor = true;
+ }
+ }
+
}
- return nearest;
+ return nearestContexts;
}
/**
- * Gets the distance to nearest good context.
- *
- * @param allContext the all context
- * @return the distance to nearest good context
+ * Return a list of contexts that have been activated by all percepts except a particular one.
+ * @param pct
+ * @return
*/
- private double getDistanceToNearestGoodContext(ArrayList<Context> allContext) {
- double d = Double.MAX_VALUE;
- for (AmoebaAgent a : allContext) {
- Context c = (Context) a;
- if (Math.abs((c.getActionProposal() - oracleValue)) <= errorAllowed && c != newContext && !c.isDying()) {
- if (getExternalDistanceToContext(c) < d) {
- d = getExternalDistanceToContext(c);
- }
+ private ArrayList<Context> getAllActivatedContextsExeptForOnePercept(Percept pct) {
+ ArrayList<Percept> percepts = new ArrayList<>(getAmas().getPercepts());
+ percepts.remove(pct);
+ ArrayList<Context> ret = new ArrayList<>(getAmas().getContexts());
+ ret.removeIf(c -> {
+ for(Percept p : percepts) {
+ if(!p.activateContext(c)) return true;
}
+ return false;
+ });
+ return ret;
+ }
+
+ private void NCS_EndogenousCompetition() {
+
+ // Creation of twin contexts to give the endogenous prediction
+
+ // 2 CTXT
+// if(activatedContexts.get(0).getInfluence(currentSituation)>activatedContexts.get(1).getInfluence(currentSituation)) {
+// highestConfidenceContext = activatedContexts.get(0);
+// secondHighestConfidenceContext = activatedContexts.get(1);
+// }
+// else {
+// highestConfidenceContext = activatedContexts.get(1);
+// secondHighestConfidenceContext = activatedContexts.get(0);
+// }
+//
+//
+// for(int i=2; i<activatedContexts.size();i++) {
+// if(activatedContexts.get(i).getInfluence(currentSituation)>highestConfidenceContext.getInfluence(currentSituation)) {
+// secondHighestConfidenceContext = highestConfidenceContext;
+// highestConfidenceContext = activatedContexts.get(i);
+// }
+// else if(activatedContexts.get(i).getInfluence(currentSituation)>secondHighestConfidenceContext.getInfluence(currentSituation)) {
+// secondHighestConfidenceContext = activatedContexts.get(i);
+// }
+// }
+//
+// contextsInCompetition.add(highestConfidenceContext);
+// contextsInCompetition.add(secondHighestConfidenceContext);
+//
+// double highestConfidenceContextInfluence = highestConfidenceContext.getInfluence(currentSituation);
+// double secondHighestConfidenceContextInfluence = secondHighestConfidenceContext.getInfluence(currentSituation);
+//
+//
+// endogenousPrediction2Contexts = (highestConfidenceContextInfluence*highestConfidenceContext.getActionProposal() + secondHighestConfidenceContextInfluence*secondHighestConfidenceContext.getActionProposal()) / (highestConfidenceContextInfluence + secondHighestConfidenceContextInfluence);
+//
+// ArrayList<Context> concernContexts = new ArrayList<Context>();
+// concernContexts.add(highestConfidenceContext);
+// concernContexts.add(secondHighestConfidenceContext);
+
+ // N CTXT
+ Double endogenousSumTerm = 0.0;
+ Double endogenousNormalizationTerm = 0.0;
+
+ Double endogenousSumTerm2 = 0.0;
+ Double endogenousNormalizationTerm2 = 0.0;
+
+ Double endogenousSumTerm3 = 0.0;
+ Double endogenousNormalizationTerm3 = 0.0;
+
+ Double endogenousSumTerm4 = 0.0;
+ Double endogenousNormalizationTerm4 = 0.0;
+
+ Double endogenousSumTerm5 = 0.0;
+ Double endogenousNormalizationTerm5 = 0.0;
+
+ ArrayList<Context> concernContexts = new ArrayList<Context>();
+ for (Context ctxt : activatedContexts) {
+ endogenousSumTerm += ctxt.getInfluenceWithConfidence(currentSituation) * ctxt.getActionProposal();
+ endogenousSumTerm2 += ctxt.getWorstInfluenceWithConfidence(currentSituation) * ctxt.getActionProposal();
+ // endogenousSumTerm3 +=
+ // ctxt.getInfluence(currentSituation)*ctxt.getActionProposal();
+ endogenousSumTerm3 += ctxt.getInfluenceWithConfidenceAndVolume(currentSituation) * ctxt.getActionProposal();
+ endogenousSumTerm4 += ctxt.getWorstInfluence(currentSituation) * ctxt.getActionProposal();
+ endogenousSumTerm5 += ctxt.getWorstInfluenceWithVolume(currentSituation) * ctxt.getActionProposal();
+ // endogenousSumTerm5 +=
+ // ctxt.getWorstInfluenceWithWorstRange(currentSituation)*ctxt.getActionProposal();
+
+ endogenousNormalizationTerm += ctxt.getInfluenceWithConfidence(currentSituation);
+ endogenousNormalizationTerm2 += ctxt.getWorstInfluenceWithConfidence(currentSituation);
+ // endogenousNormalizationTerm3 += ctxt.getInfluence(currentSituation);
+ endogenousNormalizationTerm3 += ctxt.getInfluenceWithConfidenceAndVolume(currentSituation);
+ endogenousNormalizationTerm4 += ctxt.getWorstInfluence(currentSituation);
+ endogenousNormalizationTerm5 += ctxt.getWorstInfluenceWithVolume(currentSituation);
+ // endogenousNormalizationTerm5 +=
+ // ctxt.getWorstInfluenceWithWorstRange(currentSituation);
+
+ concernContexts.add(ctxt);
}
- return d;
+ getAmas().data.endogenousPredictionActivatedContextsOverlaps = endogenousSumTerm / endogenousNormalizationTerm;
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluence = endogenousSumTerm2
+ / endogenousNormalizationTerm2;
+
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidence = endogenousSumTerm3
+ / endogenousNormalizationTerm3;
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidence = endogenousSumTerm4
+ / endogenousNormalizationTerm4;
+ getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolume = endogenousSumTerm5
+ / endogenousNormalizationTerm5;
+
+ getAmas().saver.newManualSave("Competition");
+
}
- /**
- * Gets the nearest context.
- *
- * @param allContext the all context
- * @return the nearest context
- */
- private Context getNearestContext(ArrayList<Context> allContext) {
- Context nearest = null;
- double distanceToNearest = Double.MAX_VALUE;
- for (AmoebaAgent a : allContext) {
- Context c = (Context) a;
- if (c != newContext && !c.isDying()) {
- if (nearest == null || getExternalDistanceToContext(c) < distanceToNearest) {
- nearest = c;
- distanceToNearest = getExternalDistanceToContext(c);
+ private void NCS_EndogenousSharedIncompetence() {
+ // Extrapolation of contexts by creating twin contexts that will give the
+ // prediction
+
+ ;
+
+ ContextPair<Context, Context> closestContexts = new ContextPair<Context, Context>(null, null);
+ double smallestDistanceBetweenContexts = Double.POSITIVE_INFINITY;
+ double currentDistance;
+
+ HashMap<Percept, ContextPair<Context, Context>> sharedIncompetenceContextPairs = getSharedIncompetenceContextPair();
+ for (Percept pct : sharedIncompetenceContextPairs.keySet()) {
+ if (sharedIncompetenceContextPairs.get(pct) != null) {
+ if (sharedIncompetenceContextPairs.get(pct).containTwoContexts()) {
+ currentDistance = sharedIncompetenceContextPairs.get(pct).rangeToRangeDistance(pct);
+ if (currentDistance < smallestDistanceBetweenContexts) {
+ closestContexts = sharedIncompetenceContextPairs.get(pct);
+ smallestDistanceBetweenContexts = currentDistance;
+ }
}
}
}
- return nearest;
+ double contextInfluenceL = closestContexts.getL().getInfluenceWithConfidence(currentSituation);
+ double contextInfluenceR = closestContexts.getR().getInfluenceWithConfidence(currentSituation);
+
+
+
+ if (compareClosestContextPairModels(closestContexts) < 10) {
+ getAmas().data.endogenousPredictionActivatedContextsSharedIncompetence = (contextInfluenceL
+ * closestContexts.getL().getActionProposal()
+ + contextInfluenceR * closestContexts.getR().getActionProposal())
+ / (contextInfluenceL + contextInfluenceR);
+ } else {
+ getAmas().data.endogenousPredictionActivatedContextsSharedIncompetence = getAmas().data.prediction;
+ }
+
+// double prediction = closestContexts.actionProposal(1.0);
+// if(prediction == Double.NEGATIVE_INFINITY) {
+// endogenousPrediction = - 1750.0;
+// }
+// else {
+// endogenousPrediction = prediction;
+// }
+
+ ArrayList<Context> concernContexts = new ArrayList<Context>();
+ concernContexts.add(closestContexts.getL());
+ concernContexts.add(closestContexts.getR());
+ getAmas().saver.newManualSave("SharedIncompetence");
+
+ }
+
+ private void NCSDetection_ChildContext() {
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("------------------------------------------------------------------------------------"
+ + "---------------------------------------- NCS DETECTION CHILD CONTEXT")));
+
+ if(bestContext!=null) {
+ if(!bestContext.getLocalModel().finishedFirstExperiments() && getAmas().data.firstContext && getAmas().getCycle()>0 && !bestContext.isDying()) {
+ bestContext.solveNCS_ChildContext();
+
+
+ }
+ }
+
+
+
}
+
+
- /**
- * Gets the external distance to context.
- *
- * @param context the context
- * @return the external distance to context
- */
- private double getExternalDistanceToContext(Context context) {
- double d = 0.0;
- ArrayList<Percept> percepts = amas.getPercepts();
- for (Percept p : percepts) {
- double min = context.getRanges().get(p).getStart();
- double max = context.getRanges().get(p).getEnd();
- if (min > p.getValue() || max < p.getValue()) {
- d += Math.min(Math.abs(p.getValue() - min), Math.abs(p.getValue() - max));
+ private Double compareClosestContextPairModels(ContextPair<Context, Context> closestContexts) {
+ Double difference = 0.0;
+
+ if (closestContexts.getL().getLocalModel().getCoef().length == closestContexts.getR().getLocalModel()
+ .getCoef().length) {
+ Double[] coefL = closestContexts.getL().getLocalModel().getCoef();
+ Double[] coefR = closestContexts.getR().getLocalModel().getCoef();
+ for (int i = 0; i < closestContexts.getL().getLocalModel().getCoef().length; i++) {
+ difference += Math.abs(coefL[i] - coefR[i]);
}
+ }
+ if (difference == 0.0) {
+ return Double.POSITIVE_INFINITY;
+ } else {
+ return difference;
}
- return d;
+
}
- /**
+ private void NCSDetection_Create_New_Context() {
+ /* Finally, head agent check the need for a new context agent */
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("------------------------------------------------------------------------------------"
+ + "---------------------------------------- NCS DETECTION CREATE NEX CONTEXT")));
+
+
+ boolean newContextCreated = false;
+ getAmas().data.executionTimes[9]=System.currentTimeMillis();
+ if (activatedContexts.size() == 0) {
+
+ getEnvironment().trace(TRACE_LEVEL.NCS, new ArrayList<String>(Arrays.asList(
+ "*********************************************************************************************************** SOLVE NCS CREATE NEW CONTEXT")));
+
+ getAmas().data.executionTimes[8]=System.currentTimeMillis();
+ Pair<Context, Double> nearestGoodContext = getbestContextInNeighborsWithDistanceToModel(activatedNeighborsContexts);
+ getAmas().data.executionTimes[8]=System.currentTimeMillis()- getAmas().data.executionTimes[8];
+
+
+
+ Context context;
+ if (nearestGoodContext.getA() != null) {
+ getEnvironment().trace(TRACE_LEVEL.STATE, new ArrayList<String>(Arrays.asList(nearestGoodContext.getA().getName(),
+ "************************************* NEAREST GOOD CONTEXT")));
+ context = createNewContext(nearestGoodContext.getA());
+ } else {
+ context = createNewContext();
+ }
+ // context = createNewContext();
+
+ bestContext = context;
+ newContext = context;
+ newContextCreated = true;
+
+
+ }
+ getAmas().data.executionTimes[9]=System.currentTimeMillis()- getAmas().data.executionTimes[9];
+
+
+
+
+
+
+ getAmas().data.executionTimes[10]=System.currentTimeMillis();
+ if (!newContextCreated) {
+ updateStatisticalInformations();
+ }
+ getAmas().data.executionTimes[10]=System.currentTimeMillis()- getAmas().data.executionTimes[10];
+
+
+ }
+
+ private void NCSDetection_Context_Overmapping() {
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("------------------------------------------------------------------------------------"
+ + "---------------------------------------- NCS DETECTION OVERMAPPING")));
+
+ ArrayList<Context> activatedContextsCopy = new ArrayList<Context>();
+ activatedContextsCopy.addAll(activatedContexts);
+
+ for (Context ctxt : activatedContextsCopy) {
+ if(!ctxt.isDying() && ctxt.getLocalModel().finishedFirstExperiments()) {
+ ctxt.NCSDetection_OverMapping();
+ }
+
+ }
+ }
+
+ private void NCSDetection_Concurrence() {
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("------------------------------------------------------------------------------------"
+ + "---------------------------------------- NCS DETECTION CONCURRENCE")));
+
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("bestContext != null", "" + (bestContext != null))));
+
+ if(bestContext != null) {
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("bestContext.getLocalModel().distance(bestContext.getCurrentExperiment()) < getAverageRegressionPerformanceIndicator()", "" + (bestContext.getLocalModel().distance(bestContext.getCurrentExperiment()) < getAverageRegressionPerformanceIndicator() ))));
+
+ }
+
+
+ /* If result is good, shrink redundant context (concurrence NCS) */
+ if (bestContext != null && bestContext.getLocalModel().distance(bestContext.getCurrentExperiment()) < getAverageRegressionPerformanceIndicator()) {
+ //if (bestContext != null && criticity <= predictionPerformance.getPerformanceIndicator()) {
+
+ for (int i = 0; i<activatedContexts.size();i++) {
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("activatedContexts.get(i) != bestContext", "" + ( activatedContexts.get(i) != bestContext))));
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("!activatedContexts.get(i).isDying()", "" + ( !activatedContexts.get(i).isDying()))));
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("", "" + ( activatedContexts.get(i).getLocalModel().distance(activatedContexts.get(i).getCurrentExperiment()) < getAverageRegressionPerformanceIndicator()))));
+
+ if (activatedContexts.get(i) != bestContext && !activatedContexts.get(i).isDying() && activatedContexts.get(i).getLocalModel().distance(activatedContexts.get(i).getCurrentExperiment()) < getAverageRegressionPerformanceIndicator()) {
+
+ activatedContexts.get(i).solveNCS_Concurrence(this);
+ }
+ }
+ }
+ }
+
+ private void NCSDetection_IncompetentHead() {
+ /*
+ * If there isn't any proposition or only bad propositions, the head is
+ * incompetent. It needs help from a context.
+ */
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("------------------------------------------------------------------------------------"
+ + "---------------------------------------- NCS DETECTION INCOMPETENT HEAD")));
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("bestContext != null 22", "" + (bestContext != null))));
+ if(activatedContexts.isEmpty() || ((bestContext.getLocalModel().distance(bestContext.getCurrentExperiment())) > bestContext.regressionPerformance.getPerformanceIndicator() && !oneOfProposedContextWasGood())) {
+
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("bestContext != null 23", "" + (bestContext != null))));
+ Context c = getNearestGoodContext(activatedNeighborsContexts);
+ // Context c = getSmallestGoodContext(activatedNeighborsContexts);
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("bestContext != null 24", "" + (bestContext != null))));
+
+ if (c != null) {
+ c.solveNCS_IncompetentHead(this);
+ }
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("bestContext != null 25", "" + (bestContext != null))));
+ bestContext = c;
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("bestContext != null 26", "" + (bestContext != null))));
+
+ /* This allow to test for all contexts rather than the nearest */
+ /*
+ * for (Agent a : allContexts) { Context c = (Context) a; if
+ * (Math.abs((c.getActionProposal() - oracleValue)) <= errorAllowed && c !=
+ * newContext && !c.isDying() && c != bestContext && !contexts.contains(c)) {
+ * c.growRanges(this);
+ *
+ * } }
+ */
+
+ }
+ }
+
+ private void NCSDetection_PotentialRequest() {
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("------------------------------------------------------------------------------------"
+ + "---------------------------------------- NCS DETECTION POTENTIAL REQUESTS")));
+
+ if (activatedNeighborsContexts.size() > 1) {
+ int i = 1;
+ for (Context ctxt : activatedNeighborsContexts) {
+ for (Context otherCtxt : activatedNeighborsContexts.subList(i, activatedNeighborsContexts.size())) {
+ if(!this.isDying() && !ctxt.isDying()) {
+ EndogenousRequest potentialRequest = ctxt.endogenousRequest(otherCtxt);
+ if(potentialRequest != null) {
+ addEndogenousRequest(potentialRequest);
+ }
+ }
+ }
+ i++;
+ }
+ }
+
+ getEnvironment().trace(TRACE_LEVEL.STATE, new ArrayList<String>(Arrays.asList("ENDO REQUESTS", ""+endogenousRequests.size())));
+ for(EndogenousRequest endoRequest : endogenousRequests) {
+ getEnvironment().trace(TRACE_LEVEL.STATE, new ArrayList<String>(Arrays.asList("" + endoRequest)));
+ }
+
+ }
+
+ private void selfAnalysationOfContexts4() {
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("------------------------------------------------------------------------------------"
+ + "---------------------------------------- SELF ANALYSIS OF CTXT")));
+
+ double currentDistanceToOraclePrediction;
+ double minDistanceToOraclePrediction = Double.POSITIVE_INFINITY;
+
+ for (Context activatedContext : activatedContexts) {
+ currentDistanceToOraclePrediction = activatedContext.getLocalModel().distance(activatedContext.getCurrentExperiment());
+
+
+ getAmas().data.contextNotFinished = false;
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("MODEL DISTANCE", activatedContext.getName(),
+ "" + activatedContext.getLocalModel().distance(activatedContext.getCurrentExperiment()))));
+ if (!activatedContext.getLocalModel().finishedFirstExperiments()) {
+
+ activatedContext.getLocalModel().updateModel(activatedContext.getCurrentExperiment(), getAmas().data.learningSpeed);
+ getAmas().data.contextNotFinished = true;
+
+ }
+ else if (currentDistanceToOraclePrediction < getAverageRegressionPerformanceIndicator()) {
+ //else if (currentDistanceToOraclePrediction < regressionPerformance.getPerformanceIndicator()) {
+
+ activatedContext.getLocalModel().updateModel(activatedContext.getCurrentExperiment(), getAmas().data.learningSpeed);
+
+ }
+
+ if (currentDistanceToOraclePrediction < minDistanceToOraclePrediction) {
+ minDistanceToOraclePrediction = currentDistanceToOraclePrediction;
+ getAmas().data.distanceToRegression = minDistanceToOraclePrediction;
+ }
+
+ if (!getAmas().data.contextNotFinished) {
+ criticalities.addCriticality("distanceToRegression", currentDistanceToOraclePrediction);
+
+ }
+
+ activatedContext.criticalities.addCriticality("distanceToRegression", currentDistanceToOraclePrediction);
+ //getEnvironment().trace(new ArrayList<String>(Arrays.asList("ADD CRITICALITY TO CTXT", ""+activatedContext.getName(), ""+criticalities.getLastValues().get("distanceToRegression").size())));
+
+ }
+
+
+
+ for (int i = 0; i< activatedContexts.size() ; i++) {
+
+ activatedContexts.get(i).criticalities.updateMeans();
+
+ if (activatedContexts.get(i).criticalities.getCriticalityMean("distanceToRegression") != null) {
+
+ activatedContexts.get(i).regressionPerformance.update(activatedContexts.get(i).criticalities.getCriticalityMean("distanceToRegression"));
+ getEnvironment().trace(TRACE_LEVEL.INFORM, new ArrayList<String>(Arrays.asList("UPDATE REGRESSION PERFORMANCE", activatedContexts.get(i).getName(), ""+activatedContexts.get(i).regressionPerformance.getPerformanceIndicator())));
+ }
+
+
+ activatedContexts.get(i).analyzeResults4(this);
+
+ }
+
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("NCS DECTECTION USELESSNESS IN SELF ANALISIS")));
+ for (Context ctxt : activatedNeighborsContexts) {
+
+ if (!activatedContexts.contains(ctxt)) {
+ ctxt.NCSDetection_Uselessness();
+ }
+
+ }
+ }
+
+ private void setNearestContextAsBestContext() {
+ Context nearestContext = this.getNearestContext(activatedNeighborsContexts);
+
+ if (nearestContext != null) {
+ getAmas().data.prediction = nearestContext.getActionProposal();
+ } else {
+ getAmas().data.prediction = 0.0;
+ }
+
+ bestContext = nearestContext;
+ }
+
+ /**
+ * Gets the nearest good context.
+ *
+ * @param allContext the all context
+ * @return the nearest good context
+ */
+ public Context getNearestGoodContext(ArrayList<Context> allContext) {
+ Context nearest = null;
+ for (Context c : allContext) {
+ if (Math.abs((c.getActionProposal() - getAmas().data.oracleValue)) <= getAmas().data.predictionPerformance.getPerformanceIndicator()
+ && c != newContext && !c.isDying()) {
+ if (nearest == null || getExternalDistanceToContext(c) < getExternalDistanceToContext(nearest)) {
+ nearest = c;
+ }
+ }
+ }
+
+ return nearest;
+
+ }
+
+ public Context getSmallestGoodContext(ArrayList<Context> neighbors) {
+ Context smallest = null;
+ double minVolume = Double.POSITIVE_INFINITY;
+ double currentVolume;
+ for (Context c : neighbors) {
+ currentVolume = c.getVolume();
+ if (Math.abs((c.getActionProposal() - getAmas().data.oracleValue)) <= getAmas().data.predictionPerformance.getPerformanceIndicator()
+ && c != newContext && !c.isDying()) {
+ if (smallest == null || currentVolume < minVolume) {
+ smallest = c;
+ }
+ }
+ }
+
+ return smallest;
+
+ }
+
+ private Pair<Context, Double> getbestContextInNeighborsWithDistanceToModel(ArrayList<Context> contextNeighbors) {
+ double d = Double.MAX_VALUE;
+ Context bestContextInNeighbors = null;
+
+ Double averageDistanceToModels = getAverageRegressionPerformanceIndicator();
+
+ for (Context c : contextNeighbors) {
+
+ double currentDistanceToOraclePrediction = c.getLocalModel()
+ .distance(c.getCurrentExperiment());
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("MODEL DISTANCE FOR FATHER CTXT", c.getName(),
+ "" + c.getLocalModel().distance(c.getCurrentExperiment()))));
+
+ if (currentDistanceToOraclePrediction < averageDistanceToModels) {
+ if(currentDistanceToOraclePrediction < d) {
+ d = currentDistanceToOraclePrediction;
+ bestContextInNeighbors = c;
+ }
+
+
+ }
+
+ }
+ return new Pair<Context, Double>(bestContextInNeighbors, d);
+
+ }
+
+ /**
+ * Gets the nearest context.
+ *
+ * @param allContext the all context
+ * @return the nearest context
+ */
+ private Context getNearestContext(List<Context> contextNeighboors) {
+ Context nearest = null;
+ double distanceToNearest = Double.MAX_VALUE;
+ for (Context c : contextNeighboors) {
+ if (c != newContext && !c.isDying()) {
+ double externalDistanceToContext = getExternalDistanceToContext(c);
+ if (nearest == null || externalDistanceToContext < distanceToNearest) {
+ nearest = c;
+ distanceToNearest = externalDistanceToContext;
+ }
+ }
+ }
+
+ return nearest;
+ }
+
+ /**
+ * Gets the external distance to context.
+ *
+ * @param context the context
+ * @return the external distance to context
+ */
+ private double getExternalDistanceToContext(Context context) {
+ double d = 0.0;
+ ArrayList<Percept> percepts = getAmas().getPercepts();
+ for (Percept p : percepts) {
+ if (p.isEnum()) {
+ if (!(context.getRanges().get(p).getStart() == p.getValue())) {
+ d += Double.MAX_VALUE;
+ }
+ } else {
+ double min = context.getRanges().get(p).getStart();
+ double max = context.getRanges().get(p).getEnd();
+
+ if (min > p.getValue() || max < p.getValue()) {
+ d += Math.min(Math.abs(p.getValue() - min), Math.abs(p.getValue() - max));
+ }
+ }
+
+ }
+
+ return d;
+ }
+
+ /**
+ * One of proposed context was good.
+ *
+ * @return true, if successful
+ */
+ private boolean oneOfProposedContextWasGood() {
+ boolean b = false;
+ for (Context c : activatedContexts) {
+ if (getAmas().data.oracleValue - c.getActionProposal() < getAmas().data.predictionPerformance.getPerformanceIndicator()) {
+ b = true;
+ }
+ }
+
+ return b;
+
+ }
+
+ /**
+ * Creates the new context.
+ *
+ * @return the context
+ */
+ private Context createNewContext() {
+ getAmas().data.newContextWasCreated = true;
+// if (contexts.size() != 0) {
+// System.exit(0);
+// }
+ getEnvironment().raiseNCS(NCS.CREATE_NEW_CONTEXT);
+ Context context;
+ if (getAmas().data.firstContext) {
+ context = new Context(getAmas());
+ logger().debug("HEAD", "new context agent");
+ } else {
+ context = new Context(getAmas());
+ getAmas().data.firstContext = true;
+ }
+
+ return context;
+ }
+
+ private Context createNewContext(Context bestNearestCtxt) {
+
+ getAmas().data.newContextWasCreated = true;
+ getEnvironment().raiseNCS(NCS.CREATE_NEW_CONTEXT);
+ Context context;
+ if (getAmas().data.firstContext) {
+ context = new Context(getAmas(), bestNearestCtxt);
+ logger().debug("HEAD", "new context agent");
+ } else {
+ context = new Context(getAmas());
+ getAmas().data.firstContext = true;
+ }
+
+ return context;
+ }
+
+ /**
+ * Update statistical informations.
+ */
+ private void updateStatisticalInformations() {
+
+
+ if(Math.abs(getAmas().data.oracleValue)>getAmas().data.maxPrediction) {
+ getAmas().data.maxPrediction = Math.abs(getAmas().data.oracleValue);
+ }
+
+
+ getAmas().data.normalizedCriticality = getAmas().data.criticity/getAmas().data.maxPrediction;
+ criticalities.addCriticality("predictionCriticality", getAmas().data.normalizedCriticality);
+
+ criticalities.updateMeans();
+
+ if (severalActivatedContexts()) {
+
+ endogenousCriticalities.addCriticality("predictionCriticality", getAmas().data.criticity);
+ endogenousCriticalities.addCriticality("endogenousPredictionActivatedContextsOverlapspredictionCriticality",
+ Math.abs(getAmas().data.oracleValue - getAmas().data.endogenousPredictionActivatedContextsOverlaps));
+ endogenousCriticalities.addCriticality(
+ "endogenousPredictionActivatedContextsOverlapsWorstDimInfluencepredictionCriticality",
+ Math.abs(getAmas().data.oracleValue - getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluence));
+ endogenousCriticalities.addCriticality(
+ "endogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidencepredictionCriticality",
+ Math.abs(getAmas().data.oracleValue - getAmas().data.endogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidence));
+ endogenousCriticalities.addCriticality(
+ "endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidencepredictionCriticality",
+ Math.abs(getAmas().data.oracleValue
+ - getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidence));
+ endogenousCriticalities.addCriticality(
+ "endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolumepredictionCriticality",
+ Math.abs(getAmas().data.oracleValue - getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolume));
+ endogenousCriticalities.addCriticality(
+ "endogenousPredictionActivatedContextsSharedIncompetencepredictionCriticality",
+ Math.abs(getAmas().data.oracleValue - getAmas().data.endogenousPredictionActivatedContextsSharedIncompetence));
+
+ endogenousCriticalities.updateMeans();
+
+ }
+
+ getAmas().data.predictionPerformance.update(criticalities.getCriticalityMean("predictionCriticality"));
+ if (criticalities.getCriticalityMean("distanceToRegression") != null) {
+ getAmas().data.regressionPerformance.update(criticalities.getCriticalityMean("distanceToRegression"));
+ }
+
+ // getAmas().data.mappingPerformance.update(?);
+ }
+
+ /**
+ * Gets the contexts.
+ *
+ * @return the contexts
+ */
+ public ArrayList<Context> getActivatedContexts() {
+ return activatedContexts;
+ }
+
+ /**
+ * Sets the contexts.
+ *
+ * @param contexts the new contexts
+ */
+ public void setActivatesContexts(ArrayList<Context> contexts) {
+ this.activatedContexts = contexts;
+ }
+
+ /**
+ * Select best context.
+ */
+ private void selectBestContext() {
+ if(activatedContexts != null && !activatedContexts.isEmpty()) {
+ Context bc;
+
+ bc = activatedContexts.get(0);
+ double currentConfidence = bc.getConfidence();
+
+ for (Context context : activatedContexts) {
+ if (context.getConfidence() > currentConfidence) {
+ bc = context;
+ currentConfidence = bc.getConfidence();
+ }
+ }
+ bestContext = bc;
+ } else {
+ bestContext = null;
+ }
+ }
+
+
+
+ private void selectBestContextWithDistanceToModel() {
+
+ Context bc;
+
+ bc = activatedContexts.get(0);
+ double distanceToModel = bc.getLocalModel().distance(bc.getCurrentExperiment());
+ double currentDistanceToModel;
+
+ for (Context context : activatedContexts) {
+
+ currentDistanceToModel = context.getLocalModel().distance(context.getCurrentExperiment());
+ if (currentDistanceToModel < distanceToModel) {
+ bc = context;
+ distanceToModel = currentDistanceToModel;
+ }
+ }
+ bestContext = bc;
+ }
+
+ /**
* Gets the best context.
*
* @return the best context
@@ -513,13 +1269,35 @@ public class Head extends AmoebaAgent {
return bestContext;
}
+ /**
+ * Sets the best context.
+ *
+ * @param bestContext the new best context
+ */
+ public void setBestContext(Context bestContext) {
+ this.bestContext = bestContext;
+ }
+
/**
* Gets the criticity.
*
* @return the criticity
*/
- public double getCriticity() {
- return criticity;
+ public double getCriticity() {
+ return getAmas().data.criticity;
+ }
+
+ public double getNormalizedCriticicality() {
+ return getAmas().data.normalizedCriticality;
+ }
+
+ /**
+ * Gets the no best context.
+ *
+ * @return the no best context
+ */
+ public boolean getNoBestContext() {
+ return getAmas().data.noBestContext;
}
/**
@@ -529,7 +1307,16 @@ public class Head extends AmoebaAgent {
* @return the criticity
*/
public double getCriticity(Context context) {
- return Math.abs(oracleValue - context.getActionProposal());
+ return Math.abs(getAmas().data.oracleValue - context.getActionProposal());
+ }
+
+ /**
+ * Sets the criticity.
+ *
+ * @param criticity the new criticity
+ */
+ public void setCriticity(double criticity) {
+ this.getAmas().data.criticity = criticity;
}
/**
@@ -538,16 +1325,124 @@ public class Head extends AmoebaAgent {
* @return the action
*/
public double getAction() {
- return prediction;
+ return getAmas().data.prediction;
+ }
+
+ /**
+ * Sets the action.
+ *
+ * @param action the new action
+ */
+ public void setAction(double action) {
+ this.getAmas().data.prediction = action;
+ }
+
+ /**
+ * Gets the last used context.
+ *
+ * @return the last used context
+ */
+ public Context getLastUsedContext() {
+ return lastUsedContext;
+ }
+
+ /**
+ * Sets the last used context.
+ *
+ * @param lastUsedContext the new last used context
+ */
+ public void setLastUsedContext(Context lastUsedContext) {
+ this.lastUsedContext = lastUsedContext;
+ }
+
+ /**
+ * Checks if is no creation.
+ *
+ * @return true, if is no creation
+ */
+ public boolean isNoCreation() {
+ return getAmas().data.noCreation;
+ }
+
+ /**
+ * Sets the no creation.
+ *
+ * @param noCreation the new no creation
+ */
+ public void setNoCreation(boolean noCreation) {
+ this.getAmas().data.noCreation = noCreation;
}
+ /**
+ * Gets the oracle.
+ *
+ * @return the oracle
+ */
+// public BlackBoxAgent getOracle() {
+// return oracle;
+// }
+
+ /**
+ * Sets the oracle.
+ *
+ * @param oracle the new oracle
+ */
+// public void setOracle(BlackBoxAgent oracle) {
+// this.oracle = oracle;
+// }
+
/**
* Gets the oracle value.
*
* @return the oracle value
*/
public double getOracleValue() {
- return oracleValue;
+ return getAmas().data.oracleValue;
+ }
+
+ /**
+ * Sets the oracle value.
+ *
+ * @param oracleValue the new oracle value
+ */
+ public void setOracleValue(double oracleValue) {
+ this.getAmas().data.oracleValue = oracleValue;
+ }
+
+ /**
+ * Gets the old oracle value.
+ *
+ * @return the old oracle value
+ */
+ public double getOldOracleValue() {
+ return getAmas().data.oldOracleValue;
+ }
+
+ /**
+ * Sets the old oracle value.
+ *
+ * @param oldOracleValue the new old oracle value
+ */
+ public void setOldOracleValue(double oldOracleValue) {
+ this.getAmas().data.oldOracleValue = oldOracleValue;
+ }
+
+ /**
+ * Gets the old criticity.
+ *
+ * @return the old criticity
+ */
+ public double getOldCriticity() {
+ return getAmas().data.oldCriticity;
+ }
+
+ /**
+ * Sets the old criticity.
+ *
+ * @param oldCriticity the new old criticity
+ */
+ public void setOldCriticity(double oldCriticity) {
+ this.getAmas().data.oldCriticity = oldCriticity;
}
/**
@@ -556,7 +1451,95 @@ public class Head extends AmoebaAgent {
* @return the error allowed
*/
public double getErrorAllowed() {
- return errorAllowed;
+ return getAmas().data.predictionPerformance.getPerformanceIndicator();
+ }
+
+ /**
+ * Sets the error allowed.
+ *
+ * @param errorAllowed the new error allowed
+ */
+ public void setErrorAllowed(double errorAllowed) {
+ getAmas().data.predictionPerformance.setPerformanceIndicator(errorAllowed);
+ }
+
+ /**
+ * Gets the average prediction criticity.
+ *
+ * @return the average prediction criticity
+ */
+ public double getAveragePredictionCriticity() {
+ Double mean = criticalities.getCriticalityMean("predictionCriticality");
+ if(mean == null) {
+ return 0.0;
+ }
+ else {
+ return mean;
+ }
+
+
+ }
+
+ public double getAveragePredictionCriticityCopy() {
+ return endogenousCriticalities.getCriticalityMean("predictionCriticality");
+ }
+
+ public double getAveragePredictionCriticityEndoActivatedContextsOverlaps() {
+ return endogenousCriticalities
+ .getCriticalityMean("endogenousPredictionActivatedContextsOverlapspredictionCriticality");
+ }
+
+ public double getAveragePredictionCriticityEndoActivatedContextsOverlapsWorstDimInfluence() {
+ return endogenousCriticalities.getCriticalityMean(
+ "endogenousPredictionActivatedContextsOverlapsWorstDimInfluencepredictionCriticality");
+ }
+
+ public double getAveragePredictionCriticityEndoActivatedContextsOverlapsInfluenceWithoutConfidence() {
+ return endogenousCriticalities.getCriticalityMean(
+ "endogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidencepredictionCriticality");
+ }
+
+ public double getAveragePredictionCriticityEndoActivatedContextsOverlapsWorstDimInfluenceWithoutConfidence() {
+ return endogenousCriticalities.getCriticalityMean(
+ "endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidencepredictionCriticality");
+ }
+
+ public double getAveragePredictionCriticityEndoActivatedContextsOverlapsWorstDimInfluenceWithVolume() {
+ return endogenousCriticalities.getCriticalityMean(
+ "endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolumepredictionCriticality");
+ }
+
+ public double getAveragePredictionCriticityEndoActivatedContextsSharedIncompetence() {
+ return endogenousCriticalities
+ .getCriticalityMean("endogenousPredictionActivatedContextsSharedIncompetencepredictionCriticality");
+ }
+
+ /**
+ * Sets the average prediction criticity.
+ *
+ * @param averagePredictionCriticity the new average prediction criticity
+ */
+// public void setAveragePredictionCriticity(double averagePredictionCriticity) {
+// this.averagePredictionCriticity = averagePredictionCriticity;
+// }
+
+ /**
+ * Gets the average prediction criticity weight.
+ *
+ * @return the average prediction criticity weight
+ */
+ public int getAveragePredictionCriticityWeight() {
+ return getAmas().data.averagePredictionCriticityWeight;
+ }
+
+ /**
+ * Sets the average prediction criticity weight.
+ *
+ * @param averagePredictionCriticityWeight the new average prediction criticity
+ * weight
+ */
+ public void setAveragePredictionCriticityWeight(int averagePredictionCriticityWeight) {
+ this.getAmas().data.averagePredictionCriticityWeight = averagePredictionCriticityWeight;
}
/**
@@ -568,60 +1551,389 @@ public class Head extends AmoebaAgent {
return newContext;
}
- public double getAveragePredictionCriticity() {
- return averagePredictionCriticity;
+ /**
+ * Sets the new context.
+ *
+ * @param newContext the new new context
+ */
+ public void setNewContext(Context newContext) {
+ this.newContext = newContext;
+ }
+
+ /**
+ * Change oracle connection.
+ */
+ public void changeOracleConnection() {
+ getAmas().data.useOracle = !getAmas().data.useOracle;
+ }
+
+ /**
+ * Gets the n propositions received.
+ *
+ * @return the n propositions received
+ */
+ public int getnPropositionsReceived() {
+ return getAmas().data.nPropositionsReceived;
+ }
+
+ /**
+ * Checks if is new context was created.
+ *
+ * @return true, if is new context was created
+ */
+ public boolean isNewContextWasCreated() {
+ return getAmas().data.newContextWasCreated;
+ }
+
+ /**
+ * Checks if is context from proposition was selected.
+ *
+ * @return true, if is context from proposition was selected
+ */
+ public boolean isContextFromPropositionWasSelected() {
+ return getAmas().data.contextFromPropositionWasSelected;
+ }
+
+ /**
+ * Sets the context from proposition was selected.
+ *
+ * @param contextFromPropositionWasSelected the new context from proposition was
+ * selected
+ */
+ public void setContextFromPropositionWasSelected(boolean contextFromPropositionWasSelected) {
+ this.getAmas().data.contextFromPropositionWasSelected = contextFromPropositionWasSelected;
+ }
+
+ /**
+ * Gets the prediction.
+ *
+ * @return the prediction
+ */
+ public double getPrediction() {
+ return getAmas().data.prediction;
+ }
+
+ public Double getEndogenousPredictionActivatedContextsOverlaps() {
+ return getAmas().data.endogenousPredictionActivatedContextsOverlaps;
+ }
+
+ public Double getEndogenousPredictionActivatedContextsOverlapsWorstDimInfluence() {
+ return getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluence;
+ }
+
+ public Double getEndogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidence() {
+ return getAmas().data.endogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidence;
}
- public ArrayList<Double> getxLastCriticityValues() {
- return xLastCriticityValues;
+ public Double getendogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidence() {
+ return getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidence;
+ }
+
+ public Double getEndogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolume() {
+ return getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolume;
+ }
+
+ public Double getEndogenousPredictionActivatedContextsSharedIncompetence() {
+ return getAmas().data.endogenousPredictionActivatedContextsSharedIncompetence;
+ }
+
+ public Double getEndogenousPredictionNContextsByInfluence() {
+ return getAmas().data.endogenousPredictionNContextsByInfluence;
+ }
+
+ public Double getEndogenousPredictionActivatedContextsOverlapsCriticity() {
+ return Math.abs(getAmas().data.oracleValue - getAmas().data.endogenousPredictionActivatedContextsOverlaps);
+ }
+
+ public Double getEndogenousPredictionActivatedContextsOverlapsWorstDimInfluenceCriticity() {
+ return Math.abs(getAmas().data.oracleValue - getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluence);
+ }
+
+ public Double getEndogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidenceCriticity() {
+ return Math.abs(getAmas().data.oracleValue - getAmas().data.endogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidence);
+ }
+
+ public Double getEndogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidenceCriticity() {
+ return Math.abs(getAmas().data.oracleValue - getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidence);
+ }
+
+ public Double getEndogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolumeCriticity() {
+ return Math.abs(getAmas().data.oracleValue - getAmas().data.endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolume);
+ }
+
+ public Double getEndogenousPredictionActivatedContextsSharedIncompetenceCriticity() {
+ return Math.abs(getAmas().data.oracleValue - getAmas().data.endogenousPredictionActivatedContextsSharedIncompetence);
}
/**
- * Gets the inexact allowed.
+ * Sets the prediction.
*
- * @return the inexact allowed
+ * @param prediction the new prediction
*/
- public double getInexactAllowed() {
- return inexactAllowed;
+ public void setPrediction(double prediction) {
+ this.getAmas().data.prediction = prediction;
+ }
+
+ public ArrayList<Context> getActivatedNeighborsContexts() {
+ return activatedNeighborsContexts;
+ }
+
+ public void setActivatedNeighborsContexts(ArrayList<Context> neighbors) {
+ activatedNeighborsContexts = neighbors;
+ }
+
+ public void clearAllUseableContextLists() {
+ activatedContexts.clear();
+ activatedNeighborsContexts.clear();
+ }
+
+ public Double getMaxRadiusForContextCreation(Percept pct) {
+ double maxRadius = pct.getRadiusContextForCreation();
+ double currentRadius;
+
+ // for(Context ctxt:partialNeighborContexts.get(pct)) {
+ for (Context ctxt : activatedNeighborsContexts) {
+
+ currentRadius = ctxt.getRanges().get(pct).distance(pct.getValue());
+
+ if (currentRadius < maxRadius && currentRadius > 0) {
+ maxRadius = currentRadius;
+ }
+ }
+
+ return maxRadius;
+
+ }
+
+
+ public Pair<Double, Double> getRadiusesForContextCreation(Percept pct) {
+ return new Pair<Double, Double>(
+ pct.getRadiusContextForCreation(),
+ pct.getRadiusContextForCreation());
+ }
+
+
+ public Pair<Double, Double> getMaxRadiusesForContextCreation(Percept pct) {
+// Pair<Double, Double> maxRadiuses = new Pair<Double, Double>(
+// Math.min(pct.getRadiusContextForCreation(), Math.abs(pct.getMin() - pct.getValue())),
+// Math.min(pct.getRadiusContextForCreation(), Math.abs(pct.getMax() - pct.getValue())));
+
+ Pair<Double, Double> maxRadiuses = new Pair<Double, Double>(
+ pct.getRadiusContextForCreation(),
+ pct.getRadiusContextForCreation());
+
+ //return maxRadiuses;
+
+ // Pair<Double,Double> maxRadiuses = new
+ // Pair<Double,Double>(pct.getRadiusContextForCreation(),pct.getRadiusContextForCreation());
+ // Pair<Double,Double> maxRadiuses = new
+ // Pair<Double,Double>(Math.abs(pct.getMin()-
+ // pct.getValue()),Math.abs(pct.getMax()-pct.getValue()));
+
+ double currentStartRadius;
+ double currentEndRadius;
+
+ // for(Context ctxt:partialNeighborContexts.get(pct)) {
+ for (Context ctxt : activatedNeighborsContexts) {
+
+ if (ctxt.getRanges().get(pct).centerDistance(pct.getValue()) < 0) {
+ // End radius
+ currentEndRadius = ctxt.getRanges().get(pct).distance(pct.getValue());
+ if (currentEndRadius < maxRadiuses.getB() && currentEndRadius > 0) {
+ maxRadiuses.setB(currentEndRadius);
+ }
+ }
+
+ if (ctxt.getRanges().get(pct).centerDistance(pct.getValue()) > 0) {
+ // Start radius
+ currentStartRadius = ctxt.getRanges().get(pct).distance(pct.getValue());
+ if (currentStartRadius < maxRadiuses.getA() && currentStartRadius > 0) {
+ maxRadiuses.setA(currentStartRadius);
+ }
+ }
+
+ }
+
+ return maxRadiuses;
+
+ }
+
+ public double getAverageSpatialCriticality() {
+ Double mean = criticalities.getCriticalityMean("spatialCriticality");
+ if(mean == null) {
+ return 0.0;
+ }else {
+ return mean;
+ }
}
- public int getNConflictBeforeAugmentation() {
- return nConflictBeforeAugmentation;
+ public void setBadCurrentCriticalityPrediction() {
+ getAmas().data.currentCriticalityPrediction = 1;
}
- public int getNSuccessBeforeDiminution() {
- return nSuccessBeforeDiminution;
+ public void setBadCurrentCriticalityConfidence() {
+ getAmas().data.currentCriticalityConfidence = 1;
}
- public int getNConflictBeforeInexactAugmentation() {
- return nConflictBeforeInexactAugmentation;
+ public void setBadCurrentCriticalityMapping() {
+ getAmas().data.currentCriticalityMapping = 1;
}
- public int getNSuccessBeforeInexactDiminution() {
- return nSuccessBeforeInexactDiminution;
+ public double fact(double n) {
+
+ if (n == 0) {
+ return 1;
+ } else {
+ return n * fact(n - 1);
+ }
}
- public double getAugmentationFactorError() {
- return augmentationFactorError;
+ public double combinationsWithoutRepetitions(double n) {
+ if (n == 2)
+ return 1;
+ else
+ return fact(n) / (2 * (fact(n) - 2));
}
- public double getDiminutionFactorError() {
- return diminutionFactorError;
+ public double getMappingErrorAllowed() {
+ return getAmas().data.mappingPerformance.getPerformanceIndicator();
}
- public double getMinErrorAllowed() {
- return minErrorAllowed;
+ public double getDistanceToRegression() {
+ return getAmas().data.distanceToRegression;
}
- public double getAugmentationInexactError() {
- return augmentationInexactError;
+ public double getDistanceToRegressionAllowed() {
+ return getAmas().data.regressionPerformance.getPerformanceIndicator();
+ }
+
+
+ public boolean isActiveLearning() {
+ return isSelfRequest();
+ }
+
+
+
+ public HashMap<Percept, Double> getSelfRequest(){
+ getEnvironment().trace(TRACE_LEVEL.EVENT, new ArrayList<String>(Arrays.asList("FUTURE ACTIVE LEARNING", ""+endogenousRequests.element())));
+ EndogenousRequest futureRequest = endogenousRequests.poll();
+ for(Context ctxt : futureRequest.getAskingContexts()) {
+ ctxt.deleteWaitingRequest(futureRequest);
+ }
+ return futureRequest.getRequest();
}
+
+ public void deleteRequest(Context ctxt) {
+
+ }
+
+ public boolean isSelfRequest(){
+ return endogenousRequests.size()>0;
+ }
+
+ public void addSelfRequest(HashMap<Percept, Double> request, int priority, Context ctxt){
+
+ addEndogenousRequest(new EndogenousRequest(request, null, priority,new ArrayList<Context>(Arrays.asList(ctxt)), REQUEST.SELF));
+ }
+
+ public void addEndogenousRequest(EndogenousRequest request) {
+
+ boolean existingRequestTest = false;
+
+ if(request.getAskingContexts().size()>1) {
+
+ Iterator<EndogenousRequest> itr = endogenousRequests.iterator();
+ while(!existingRequestTest && itr.hasNext()) {
+
+ EndogenousRequest currentRequest = itr.next();
+
+ if(currentRequest.getType() == REQUEST.CONFLICT || currentRequest.getType() == REQUEST.CONCURRENCE) {
+
+ existingRequestTest = existingRequestTest || currentRequest.testIfContextsAlreadyAsked(request.getAskingContexts());
+ }
+ if(currentRequest.getType() == REQUEST.VOID) {
+ existingRequestTest = existingRequestTest || currentRequest.requestInBounds(request.getRequest());
+ }
+
+ }
+ if(!existingRequestTest) {
+ for(Context ctxt : request.getAskingContexts()) {
+ ctxt.addWaitingRequest(request);
+ }
+ endogenousRequests.add(request);
+ getEnvironment().trace(TRACE_LEVEL.EVENT, new ArrayList<String>(Arrays.asList("NEW ADDED ENDO REQUEST", ""+request)));
+ }
+ }else {
+ request.getAskingContexts().get(0).addWaitingRequest(request);
+ endogenousRequests.add(request);
+ getEnvironment().trace(TRACE_LEVEL.EVENT, new ArrayList<String>(Arrays.asList("NEW ADDED ENDO REQUEST", ""+request)));
+ }
+
+
+
+ }
+
+ public boolean isRealVoid(HashMap<Percept, Double> request) {
+ boolean test;
+
+ for(Context ctxt : activatedNeighborsContexts) {
+
+
+
+ test = true;
+ for(Percept pct : getAmas().getPercepts()) {
+// test = test && ctxt.getRanges().get(pct).contains2(request.get(pct));
+ test = test && ctxt.getRanges().get(pct).contains(request.get(pct), pct.getMappingErrorAllowedMin());
+ }
+
+ getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("IS REAL VOID",ctxt.getName(), "-->", ""+!test)));
+
+ if(test) {
+ return false;
+ }
+ }
+ return true;
+
+
+ }
+
+ public Double getAverageRegressionPerformanceIndicator() {
+
+ return getAmas().data.averageRegressionPerformanceIndicator;
+
+ }
+
+ public void setAverageRegressionPerformanceIndicator() {
+
+ int numberOfRegressions = 0;
+ if(activatedNeighborsContexts.size()>0) {
+ double meanRegressionPerformanceIndicator = 0.0;
+ for(Context ctxt : activatedNeighborsContexts) {
+ meanRegressionPerformanceIndicator += ctxt.regressionPerformance.performanceIndicator;
+ numberOfRegressions+=1;
+ }
+ assert numberOfRegressions != 0;
+ getAmas().data.averageRegressionPerformanceIndicator = (meanRegressionPerformanceIndicator/numberOfRegressions > getAmas().data.initRegressionPerformance) ? meanRegressionPerformanceIndicator/numberOfRegressions : getAmas().data.initRegressionPerformance;
+ }
+ else{
+ getAmas().data.averageRegressionPerformanceIndicator = getAmas().data.initRegressionPerformance;
+ }
+
+ }
+
- public double getDiminutionInexactError() {
- return diminutionInexactError;
+ public void proposition(Context c) {
+ activatedContexts.add(c);
}
+
+ @Override
+ protected void onInitialization() {
+ super.onInitialization();
+ getAmas().data.maxConfidence = Double.NEGATIVE_INFINITY;
+ getAmas().data.minConfidence = Double.POSITIVE_INFINITY;
- public double getMinInexactAllowed() {
- return minInexactAllowed;
+ criticalities = new Criticalities(getAmas().data.numberOfCriticityValuesForAverage);
+ endogenousCriticalities = new Criticalities(getAmas().data.numberOfCriticityValuesForAverageforVizualisation);
}
+
}
diff --git a/AMOEBAonAMAK/src/agents/head/REQUEST.java b/AMOEBAonAMAK/src/agents/head/REQUEST.java
new file mode 100644
index 0000000000000000000000000000000000000000..64ec5f2d25528b862f3fb52151d431d68066335c
--- /dev/null
+++ b/AMOEBAonAMAK/src/agents/head/REQUEST.java
@@ -0,0 +1,18 @@
+package agents.head;
+
+import java.io.Serializable;
+
+public enum REQUEST implements Serializable {
+
+ OVERLAP,
+ CONFLICT,
+ CONCURRENCE,
+ VOID,
+ SELF
+
+}
+
+
+
+
+
diff --git a/AMOEBAonAMAK/src/agents/percept/ContextProjection.java b/AMOEBAonAMAK/src/agents/percept/ContextProjection.java
index 422c64659f72d67b0d72a86f5751a6d665299476..82556e3e5c520ab1500a64191f06ed397fb1bd52 100644
--- a/AMOEBAonAMAK/src/agents/percept/ContextProjection.java
+++ b/AMOEBAonAMAK/src/agents/percept/ContextProjection.java
@@ -1,13 +1,28 @@
package agents.percept;
+import java.io.Serializable;
+import java.util.ArrayList;
+import java.util.Arrays;
+
import agents.context.Context;
+import kernel.World;
+
+public class ContextProjection implements Serializable {
-public class ContextProjection {
private Percept percept;
private Context context;
+
private double start;
private double end;
+ // For testing only //
+ public ContextProjection(double start, double end) {
+ this.percept = null;
+ this.context = null;
+ this.start = start;
+ this.end = end;
+ }
+
public ContextProjection(Percept percept, Context context) {
this.percept = percept;
this.context = context;
@@ -15,6 +30,19 @@ public class ContextProjection {
this.end = context.getRanges().get(this.percept).getEnd();
}
+ public void setRanges(double start, double end) {
+ this.start = start;
+ this.end = end;
+ }
+
+ public void setRangeStart(double start) {
+ this.start = start;
+ }
+
+ public void setRangeEnd(double end) {
+ this.end = end;
+ }
+
public void updateStart() {
this.start = context.getRanges().get(this.percept).getStart();
}
@@ -23,11 +51,77 @@ public class ContextProjection {
this.end = context.getRanges().get(this.percept).getEnd();
}
+ public String getRanges() {
+ return "{" + start + " , " + end + "}";
+ }
+
+ public double getRanges(String range) {
+ if (range.equals("start")) {
+ return this.start;
+ } else if (range.equals("end")) {
+ return this.end;
+ } else {
+ return 0;
+ }
+ }
+
public boolean contains(Double value) {
- return (value > start) && (value < end);
+ // world.trace(new
+ // ArrayList<String>(Arrays.asList(context.getName(),percept.getName(),
+ // ""+value, ""+(getCenter()-getRadius()), ""+ (getCenter() + getRadius()))));
+ return Math.abs(value - getCenter()) <= getRadius();
+ }
+
+ public boolean contains(Double value, Double neighborhood) {
+// System.out.println(context.getName() +" "+ percept.getName() + " " + value +
+// " " + (start - neighborhood) + " " + start + " " + end + " " + (end +
+// neighborhood));
+ return Math.abs(value - getCenter()) < (getRadius() + neighborhood);
+ }
+
+ public boolean inNeighborhoodOf(Double value) {
+ return Math.abs(value - this.getCenter()) < 2 * getNeighboorhood();
+ }
+
+ public double distance(ContextProjection ctxtPrjct) {
+ double contextCenter1 = this.getCenter();
+ double contextCenter2 = ctxtPrjct.getCenter();
+ double contextRadius1 = this.getRadius();
+ double contextRadius2 = ctxtPrjct.getRadius();
+ return Math.abs(contextCenter1 - contextCenter2) - contextRadius1 - contextRadius2;
}
public Context getContext() {
return this.context;
}
+
+ public String toString() {
+ return "{" + this.start + " , " + this.end + "}";
+ }
+
+ public double getRadius() {
+ return (end - start) / 2;
+ }
+
+ public double getCenter() {
+ return (end + start) / 2;
+ }
+
+ public double getNeighboorhood() {
+ return getRadius();
+ }
+
+ public boolean inNeighborhood() {
+ return this.contains(percept.getValue(), context.getEnvironment().getContextCreationNeighborhood(context, percept))
+ || this.contains(percept.getValue(), this.getRadius() / 2);
+ }
+
+ public double getStart() {
+ return start;
+ }
+
+ public double getEnd() {
+ return end;
+ }
+
}
diff --git a/AMOEBAonAMAK/src/agents/percept/Percept.java b/AMOEBAonAMAK/src/agents/percept/Percept.java
index 06a98335f20519530fcafa67ade7f7e9c153c261..2820e695eecb8c41accb4e9fb7d4b2a1d2ed68ee 100644
--- a/AMOEBAonAMAK/src/agents/percept/Percept.java
+++ b/AMOEBAonAMAK/src/agents/percept/Percept.java
@@ -1,169 +1,424 @@
-package agents.percept;
-
-import java.util.HashMap;
-import java.util.HashSet;
-
-import agents.AmoebaAgent;
-import agents.context.Context;
-import kernel.AMOEBA;
-
-/**
- * Percept agent is in charge of the communication with the environment.
- * Each Percept agent must be connected to one data source.
- *
- */
-public class Percept extends AmoebaAgent {
- private HashMap<Context, ContextProjection> contextProjections = new HashMap<Context, ContextProjection>();
- private HashSet<Context> validContextProjection = new HashSet<Context>();
-
- private double min = Double.MAX_VALUE;
- private double max = Double.MIN_VALUE;
-
- private double value;
- private boolean isEnum;
-
- public Percept(AMOEBA amas) {
- super(amas);
- this.isEnum = false;
- }
-
- @Override
- protected void onAct() {
- value = amas.getPerceptions(name);
- ajustMinMax();
- computeContextProjectionValidity();
- }
-
- public void computeContextProjectionValidity() {
- /* The algorithm used here :
- *
- * Variables :
- * global set allContexts
- * global set validContexts
- * local set myValidContexts
- *
- * Algorithm : for each percept do :
- * myValidContexts <- validContexts
- * if myValidContexts = null then
- * myValidContexts <- allContexts
- * fi
- *
- * for context in myValidContext do
- * if not isValid(context) then
- * myValidContexts.remove(context)
- * fi
- * done
- *
- * validContexts <- intersect(validContexts, myValidContexts)
- * #we use an intersect to allow multithreading, avoiding that a percept override the work of another
- *
- */
-
-
- validContextProjection = new HashSet<Context>();
-
- // To avoid unnecessary tests, we only compute validity on context
- // validated by percepts that have finished before us
- HashSet<Context> contexts = amas.getValidContexts();
- if(contexts == null) {
- // If we are one of the first percept to run, we compute validity on all contexts
- contexts = new HashSet<>(amas.getContexts());
- }
-
- for (Context c : contexts) {
- if (contextProjections.get(c).contains(this.value)) {
- validContextProjection.add(c);
- }
- }
- amas.updateValidContexts(validContextProjection);
-
- logger().debug("CYCLE "+getAmas().getCycle(), "%s's valid contexts : %s", toString(), validContextProjection.toString());
- }
-
- /**
- * Allow the percept to record the lower and higher value perceived.
- */
- public void ajustMinMax() {
- if (value < min) {
- min = value;
- }
- if (value > max) {
- max = value;
- }
-
- /*
- * In order to avoid big gap in min-max value in order to adapt with the system
- * dynamic It's also a warranty to avoid to flaw AVT with flawed value
- */
- double dist = max - min;
- min += 0.05 * dist;
- max -= 0.05 * dist;
- }
-
- /**
- * Gets the min max distance.
- *
- * @return the min max distance
- */
- public double getMinMaxDistance() {
- if (min == Double.MAX_VALUE || max == Double.MIN_VALUE)
- return 0;
- return Math.abs(max - min);
- }
-
- /**
- * Gets the value.
- *
- * @return the value
- */
- public double getValue() {
- return value;
- }
-
- /**
- * Set the value of the percept.
- * Useful when loading a save.
- *
- * @param value
- */
- public void setValue(double value) {
- this.value = value;
- }
-
- /**
- * Checks if is enum.
- *
- * @return true, if is enum
- */
- public boolean isEnum() {
- return isEnum;
- }
-
- public void setEnum(boolean isEnum) {
- this.isEnum = isEnum;
- }
-
- /*
- * Context projection methods
- */
- public void addContextProjection(Context context) {
- ContextProjection newContextProjection = new ContextProjection(this, context);
- contextProjections.put(context, newContextProjection);
- }
-
- public void deleteContextProjection(Context context) {
- contextProjections.remove(context);
- }
-
- public void updateContextProjectionStart(Context context) {
- contextProjections.get(context).updateStart();
- }
-
- public void updateContextProjectionEnd(Context context) {
- contextProjections.get(context).updateEnd();
- }
- @Override
- public String toString() {
- return getName();
- }
-}
+package agents.percept;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.HashSet;
+
+import agents.AmoebaAgent;
+import agents.context.Context;
+import kernel.AMOEBA;
+
+/**
+ * Percept agent is in charge of the communication with the environment. Each
+ * Percept agent must be connected to one data source.
+ *
+ */
+public class Percept extends AmoebaAgent {
+
+ // private BlackBoxAgent sensor;
+ protected ArrayList<AmoebaAgent> targets = new ArrayList<>();
+ protected ArrayList<Context> activatedContext = new ArrayList<>();
+
+ public HashMap<Context, ContextProjection> contextProjections = new HashMap<Context, ContextProjection>();
+ private HashSet<Context> validContextProjection = new HashSet<Context>();
+ private HashSet<Context> neighborContextProjection = new HashSet<Context>();
+
+ private double min = Double.POSITIVE_INFINITY;
+ private double max = Double.NEGATIVE_INFINITY;
+
+
+ private double value;
+ private boolean isEnum = false;
+
+ /**
+ * Instantiates a new percept.
+ *
+ * @param amoeba
+ */
+ public Percept(AMOEBA amoeba) {
+ super(amoeba);
+ getAmas().addPercept(this);
+ }
+
+ /**
+ * Instanriates a new percept, not linked to any amoeba.
+ * USE FOR VISUALIZATION ONLY
+ */
+ public Percept() {
+ super(null);
+ }
+
+ @Override
+ public void onAct() {
+ value = getAmas().getPerceptions(this.name);
+ ajustMinMax();
+ computeContextProjectionValidityOptimized();
+ }
+
+ public void computeContextProjectionValidityOptimized() {
+
+ /* The algorithm used here :
+ *
+ * Variables :
+ * global set allContexts
+ * global set validContexts
+ * local set myValidContexts
+ *
+ * Algorithm : for each percept do :
+ * myValidContexts <- validContexts
+ * if myValidContexts = null then
+ * myValidContexts <- allContexts
+ * fi
+ *
+ * for context in myValidContext do
+ * if not isValid(context) then
+ * myValidContexts.remove(context)
+ * fi
+ * done
+ *
+ * validContexts <- intersect(validContexts, myValidContexts)
+ * #we use an intersect to allow multithreading, avoiding that a percept override the work of another
+ *
+ */
+
+ validContextProjection = new HashSet<Context>();
+ neighborContextProjection = new HashSet<Context>();
+
+ // To avoid unnecessary tests, we only compute validity on context
+ // validated by percepts that have finished before us
+ HashSet<Context> contexts = amas.getValidContexts();
+ if(contexts == null) {
+ // If we are one of the first percept to run, we compute validity on all contexts
+ contexts = new HashSet<>(amas.getContexts());
+ }
+
+ for (Context c : contexts) {
+ if (activateContext(c)) {
+ validContextProjection.add(c);
+ }
+ }
+ amas.updateValidContexts(validContextProjection);
+
+ HashSet<Context> neighborsContexts = amas.getNeighborContexts();
+ if(neighborsContexts == null) {
+ // If we are one of the first percept to run, we compute validity on all contexts
+ neighborsContexts = new HashSet<>(amas.getContexts());
+ }
+
+ for (Context c : neighborsContexts) {
+ if(inNeighborhood(c)) {
+ neighborContextProjection.add(c);
+ }
+ }
+ amas.updateNeighborContexts(neighborContextProjection);
+
+ logger().debug("CYCLE "+getAmas().getCycle(), "%s's valid contexts : %s", toString(), validContextProjection.toString());
+ }
+
+ /**
+ * Return true if the context is activated by this percept.
+ * @param context
+ * @return
+ */
+ public boolean activateContext(Context context) {
+ return contextProjections.get(context).contains(this.value);
+ }
+
+ /**
+ * Return true if the context is in the neighborhood of this percept.
+ * @param context
+ * @return
+ */
+ public boolean inNeighborhood(Context context) {
+ return contextProjections.get(context).inNeighborhood();
+ }
+
+
+ /**
+ * Allow the percept to record the lower and higher value perceived.
+ */
+ public void ajustMinMax() {
+ if (value < min)
+ min = value;
+ if (value > max)
+ max = value;
+ }
+
+ /**
+ * Gets the min max distance.
+ *
+ * @return the min max distance
+ */
+ public double getMinMaxDistance() {
+ if (min == Double.MAX_VALUE || max == Double.MIN_VALUE)
+ return 0;
+ return Math.abs(max - min);
+ }
+
+ public double getMin() {
+ if (min == Double.MAX_VALUE) {
+ return 0.0;
+ }
+ return min;
+ }
+
+ public double getMax() {
+ if (max == Double.MIN_VALUE) {
+ return 0.0;
+ }
+ return max;
+ }
+
+ public void setMin(double value) {
+ min = value;
+ }
+
+ public void setMax(double value) {
+ max = value;
+ }
+
+ /**
+ * Gets the activated context.
+ *
+ * @return the activated context
+ */
+ public ArrayList<Context> getActivatedContext() {
+ return activatedContext;
+ }
+
+ /**
+ * Sets the activated context.
+ *
+ * @param activatedContext the new activated context
+ */
+ public void setActivatedContext(ArrayList<Context> activatedContext) {
+ this.activatedContext = activatedContext;
+ }
+
+ /**
+ * Gets the value.
+ *
+ * @return the value
+ */
+ public double getValue() {
+ return value;
+ }
+
+ /**
+ * Sets the value.
+ *
+ * @param value the new value
+ */
+ public void setValue(double value) {
+ this.value = value;
+ }
+
+ /*
+ * (non-Javadoc)
+ *
+ * @see agents.SystemAgent#getTargets()
+ */
+ public ArrayList<? extends AmoebaAgent> getTargets() {
+ return targets;
+ }
+
+ /**
+ * Sets the targets.
+ *
+ * @param targets the new targets
+ */
+ public void setTargets(ArrayList<AmoebaAgent> targets) {
+ this.targets = targets;
+ }
+
+
+
+
+
+ /**
+ * Checks if is enum.
+ *
+ * @return true, if is enum
+ */
+ public boolean isEnum() {
+ return isEnum;
+ }
+
+ /**
+ * Sets the enum.
+ *
+ * @param isEnum the new enum
+ */
+ public void setEnum(boolean isEnum) {
+ this.isEnum = isEnum;
+ }
+
+ /*
+ * Context projection methods
+ */
+
+ public void addContextProjection(Context context) {
+ ContextProjection newContextProjection = new ContextProjection(this, context);
+ contextProjections.put(context, newContextProjection);
+
+ }
+
+ public void deleteContextProjection(Context context) {
+ contextProjections.remove(context);
+ //////// System.out.println("DELETION
+ //////// ------------------------------------------------------------------------------------------------------"
+ //////// + world.getScheduler().getTick());
+ //////// System.out.println(context.getName());
+ //////// System.out.println("----------------------------------------------------------------------------------------------------------------");
+ }
+
+ public void updateContextProjectionStart(Context context) {
+ //////// System.out.println(context.getName());
+ //////// System.out.println(contextProjections.get(context));
+ //////// System.out.println(contextProjections.size() + " " +
+ //////// world.getScheduler().getContextsAsContext().size());
+ if (!context.isDying()) {
+ contextProjections.get(context).updateStart();
+ }
+
+ }
+
+ public void updateContextProjectionEnd(Context context) {
+ if (!context.isDying()) {
+ contextProjections.get(context).updateEnd();
+ }
+
+ }
+
+ public boolean overlapBetweenContexts(Context context1, Context context2) {
+
+ double contextStart1 = getStartRangeProjection(context1);
+ double contextStart2 = getStartRangeProjection(context2);
+ double contextEnd1 = getEndRangeProjection(context1);
+ double contextEnd2 = getEndRangeProjection(context2);
+ ////////// System.out.println(context1.getName() + " " + contextStart1 + " " +
+ ////////// contextEnd1 + " " + context2.getName() + " " + contextStart2 + " " +
+ ////////// contextEnd2);
+ return ((contextStart1 < contextStart2 && contextStart2 < contextEnd1)
+ || ((contextStart1 < contextEnd2 && contextEnd2 < contextEnd1)))
+ || ((contextStart2 < contextStart1 && contextStart1 < contextEnd2)
+ || ((contextStart2 < contextEnd1 && contextEnd1 < contextEnd2)));
+
+ }
+
+ public double getRangeProjection(Context context, String range) {
+ if (range.equals("start")) {
+ return context.getRanges().get(this).getStart();
+ } else if (range.equals("end")) {
+ return context.getRanges().get(this).getEnd();
+ } else {
+ return 0;
+ }
+
+ }
+
+ public Double getEndRangeProjection(Context context) {
+ return new Double(context.getRanges().get(this).getEnd());
+ }
+
+ public Double getStartRangeProjection(Context context) {
+ return new Double(context.getRanges().get(this).getStart());
+ }
+
+ public HashMap<String, Double> getOverlapRangesBetweenContexts(Context context1, Context context2) {
+
+ HashMap<String, Double> overlapRanges = new HashMap<String, Double>();
+
+ if (contextIncludedIn(context1, context2)) {
+ overlapRanges.put("start", getStartRangeProjection(context1));
+ overlapRanges.put("end", getEndRangeProjection(context1));
+ } else if (contextIncludedIn(context2, context1)) {
+ overlapRanges.put("start", getStartRangeProjection(context2));
+ overlapRanges.put("end", getEndRangeProjection(context2));
+ } else if (contextOrder(context1, context2)) {
+ overlapRanges.put("start", getStartRangeProjection(context2));
+ overlapRanges.put("end", getEndRangeProjection(context1));
+ } else if (contextOrder(context2, context1)) {
+ overlapRanges.put("start", getStartRangeProjection(context1));
+ overlapRanges.put("end", getEndRangeProjection(context2));
+ } else {
+ ////////// System.out.println("PROBLEM !!!!!!!!!!!!!!!!! " + context1.getName()
+ ////////// + " " + getStartRangeProjection(context1) + " " +
+ ////////// getEndRangeProjection(context1) + " " + context2.getName() + " " +
+ ////////// getStartRangeProjection(context2) + " " +
+ ////////// getEndRangeProjection(context2));
+ overlapRanges.put("start", -1.0);
+ overlapRanges.put("end", 1.0);
+ // return null;
+ }
+
+ return overlapRanges;
+ }
+
+ public boolean contextIncludedIn(Context includedContext, Context includingContext) {
+
+ double includedContextStart = getStartRangeProjection(includedContext);
+ double includingContextStart = getStartRangeProjection(includingContext);
+ double includedContextEnd = getEndRangeProjection(includedContext);
+ double includingContextEnd = getEndRangeProjection(includingContext);
+
+ return ((includingContextStart < includedContextStart && includedContextStart < includingContextEnd)
+ && ((includingContextStart < includedContextEnd && includedContextEnd < includingContextEnd)));
+ }
+
+ public boolean contextOrder(Context context1, Context context2) {
+
+ double contextStart1 = getStartRangeProjection(context1);
+ double contextEnd1 = getEndRangeProjection(context1);
+
+ double contextStart2 = getStartRangeProjection(context2);
+ double contextEnd2 = getEndRangeProjection(context2);
+
+ // world.trace(new
+ // ArrayList<String>(Arrays.asList(""+contextStart1,""+contextStart2,
+ // ""+contextEnd1, ""+(contextStart1 <= contextStart2 && contextStart2 <=
+ // contextEnd1))));
+
+ return (contextStart1 <= contextStart2 && contextStart2 <= contextEnd1 && contextEnd1 <= contextEnd2);
+ }
+
+ public Percept clone() throws CloneNotSupportedException {
+ return (Percept) super.clone();
+ }
+
+ public double getRadiusContextForCreation() {
+ // return 200*world.getContextCreationPercentage();
+ return getMinMaxDistance() * getEnvironment().getMappingErrorAllowed();
+ }
+
+ public double getMappingErrorAllowed() {
+ return getMinMaxDistance() * getEnvironment().getMappingErrorAllowed();
+ }
+
+ public double getMappingErrorAllowedMin() {
+ return getMinMaxDistance() * getEnvironment().getMappingErrorAllowed() * 0.4;
+ }
+
+ public double getMappingErrorAllowedOverMapping() {
+ return getMinMaxDistance() * getEnvironment().getMappingErrorAllowed() * 0.5;
+ }
+
+ public double getMappingErrorAllowedMax() {
+ return getMinMaxDistance() * getEnvironment().getMappingErrorAllowed() * 1.5;
+ }
+
+ // -----------------------
+ // AMOEBAonAMAK code ----
+ // -----------------------
+
+ @Override
+ public String toString() {
+ return getName();
+ }
+
+ @Override
+ public void destroy() {
+ super.destroy();
+ getAmas().setPercepts();
+ }
+}
diff --git a/AMOEBAonAMAK/src/experiments/AdvancedMain.java b/AMOEBAonAMAK/src/experiments/AdvancedMain.java
index da18909d3004fa1d43d1de6877f74661da531e11..d0267bb169fd4cb920fb0d8ae0dd01ab69ffec4c 100644
--- a/AMOEBAonAMAK/src/experiments/AdvancedMain.java
+++ b/AMOEBAonAMAK/src/experiments/AdvancedMain.java
@@ -10,10 +10,10 @@ import javafx.beans.value.ChangeListener;
import javafx.beans.value.ObservableValue;
import javafx.scene.control.Slider;
import kernel.AMOEBA;
-import kernel.BackupSystem;
-import kernel.IBackupSystem;
-import kernel.SaveHelper;
import kernel.StudiedSystem;
+import kernel.backup.BackupSystem;
+import kernel.backup.IBackupSystem;
+import kernel.backup.SaveHelperImpl;
/**
* A more advanced and complete main.
@@ -34,7 +34,7 @@ public class AdvancedMain {
// Set AMAK configuration before creating an AMOEBA
Configuration.commandLineMode = false;
- Configuration.allowedSimultaneousAgentsExecution = 8;
+ Configuration.allowedSimultaneousAgentsExecution = 1;
Configuration.waitForGUI = true;
// Create an AMOEBA
@@ -59,7 +59,7 @@ public class AdvancedMain {
// We add an optional saver, allowing us to autosave the amoeba at each cycle.
// The SaveHelper also add graphical tools to save and load AMOEBA's state.
- amoeba.saver = new SaveHelper(amoeba);
+ amoeba.saver = new SaveHelperImpl(amoeba);
// Autosave slow execution, if you want fast training, set saver to null,
// or saver.autoSave = false.
diff --git a/AMOEBAonAMAK/src/experiments/Benchmark.java b/AMOEBAonAMAK/src/experiments/Benchmark.java
index 42eeca653ee7820b98471fcbd27895729efa59ad..17c5376ea16351c8290ce2ca1e704656b83408ba 100644
--- a/AMOEBAonAMAK/src/experiments/Benchmark.java
+++ b/AMOEBAonAMAK/src/experiments/Benchmark.java
@@ -6,8 +6,8 @@ import java.util.ArrayList;
import fr.irit.smac.amak.Configuration;
import fr.irit.smac.amak.tools.Log;
import kernel.AMOEBA;
-import kernel.BackupSystem;
import kernel.StudiedSystem;
+import kernel.backup.BackupSystem;
public class Benchmark {
diff --git a/AMOEBAonAMAK/src/experiments/BenchmarkThreading.java b/AMOEBAonAMAK/src/experiments/BenchmarkThreading.java
index 668b75cdcc73ecd4227eb9a2f4079315b713edad..58529462bf7b4a9ae7054e3d2860d7408c912bea 100644
--- a/AMOEBAonAMAK/src/experiments/BenchmarkThreading.java
+++ b/AMOEBAonAMAK/src/experiments/BenchmarkThreading.java
@@ -9,10 +9,10 @@ import java.util.function.DoubleBinaryOperator;
import fr.irit.smac.amak.Configuration;
import fr.irit.smac.amak.tools.Log;
import kernel.AMOEBA;
-import kernel.BackupSystem;
import kernel.IAMOEBA;
-import kernel.IBackupSystem;
import kernel.StudiedSystem;
+import kernel.backup.BackupSystem;
+import kernel.backup.IBackupSystem;
public class BenchmarkThreading {
diff --git a/AMOEBAonAMAK/src/experiments/FILE.java b/AMOEBAonAMAK/src/experiments/FILE.java
new file mode 100644
index 0000000000000000000000000000000000000000..d4c5f048aaff94e6bafa8f8e46b8ac32d38a7aa5
--- /dev/null
+++ b/AMOEBAonAMAK/src/experiments/FILE.java
@@ -0,0 +1,87 @@
+package experiments;
+
+
+//Packages a importer afin d'utiliser l'objet File
+
+import java.io.FileNotFoundException;
+import java.io.PrintWriter;
+import java.util.ArrayList;
+import java.util.Arrays;
+
+public class FILE {
+
+ PrintWriter pw;
+
+ String manualMessage;
+
+ public FILE(String folder, String name){
+ try {
+ pw = new PrintWriter("C:/Users/dato/Documents/THESE/XP/"+ folder + "/" + name + ".csv");
+ } catch (FileNotFoundException e) {
+ // TODO Auto-generated catch block
+ e.printStackTrace();
+ }
+ }
+
+
+ public void write(Double f1, Double f2){
+ pw.println(f1.toString() + ";" + f2.toString());
+ }
+
+ public void write(Double f1, Double f2, Double f3){
+ pw.println(f1.toString() + ";" + f2.toString() + ";" + f3.toString());
+ }
+
+ public void write(Double f1, Double f2, Double f3, Double f4){
+ pw.println(f1.toString() + ";" + f2.toString() + ";" + f3.toString() + ";" + f4.toString());
+ }
+
+ public void close(){
+ pw.close();
+ }
+
+ public void write(ArrayList<String> infos) {
+ String message = "";
+ for(String info : infos) {
+ message += info + ";" ;
+ }
+ pw.println(message);
+ }
+
+ public void write(ArrayList<String> context, ArrayList<String> infos) {
+ String message = "";
+ for(String ctxt : context) {
+ message += ctxt + ";" ;
+ }
+ for(String info : infos) {
+ message += info + ";" ;
+ }
+ pw.println(message);
+ }
+
+ public void initManualMessage() {
+ manualMessage = "";
+ }
+
+ public void addManualMessage(String subMessage) {
+ manualMessage += subMessage + ";";
+ }
+
+ public void sendManualMessage() {
+ pw.println(manualMessage);
+ }
+
+public static void main(String[] args) {
+
+ FILE test = new FILE("Regression","test");
+
+ test.write(0.0000d, 0.0045d);
+ test.write(0.0000d, 0.0045d);
+
+ test.write(new ArrayList<String>(Arrays.asList(""+185.0, ""+0.1111,""+0.5454)));
+ test.write(new ArrayList<String>(Arrays.asList(""+185.0, ""+0.1111,""+0.5454,""+0.545)));
+
+ test.close();
+}
+
+}
diff --git a/AMOEBAonAMAK/src/experiments/F_XY_System.java b/AMOEBAonAMAK/src/experiments/F_XY_System.java
index 9e9b4f3517b232ff4850b18dc4d24ed17a831c13..8aba6d446a4bb86d6aea058b234028ff40b8adac 100644
--- a/AMOEBAonAMAK/src/experiments/F_XY_System.java
+++ b/AMOEBAonAMAK/src/experiments/F_XY_System.java
@@ -1,58 +1,83 @@
-package experiments;
-
-import java.util.HashMap;
-import java.util.Random;
-
-import kernel.StudiedSystem;
-
-/**
- * The Class BadContextManager.
- */
-public class F_XY_System implements StudiedSystem {
-
- /** The x. */
- double x = 0;
- /** The y. */
- double y = 0;
- /** The result. */
- double result = 0;
- /** The first step. */
- boolean firstStep = true;
- double spaceSize;
- Random generator;
-
- public F_XY_System(double size) {
- this.spaceSize = size;
- }
-
- private double getResult(double x, double y) {
- return (y > -spaceSize && y < spaceSize && x < spaceSize && x > -spaceSize) ? 2 * x + y : 5 * x - 8 * y;
- }
-
- @Override
- public void playOneStep() {
- if (generator == null) {
- generator = new Random(29);
- }
-
- x = (generator.nextDouble() - 0.5) * spaceSize * 4;
- y = (generator.nextDouble() - 0.5) * spaceSize * 4;
- }
-
- @Override
- public HashMap<String, Double> getOutput() {
- HashMap<String, Double> out = new HashMap<String, Double>();
-
- result = getResult(x, y);
-
- out.put("px", x);
- out.put("py", y);
- out.put("oracle", result);
- return out;
- }
-
- @Override
- public double requestOracle(HashMap<String, Double> request) {
- return getResult(request.get("px"), request.get("py"));
- }
+package experiments;
+
+import java.util.HashMap;
+import java.util.Random;
+
+import agents.percept.Percept;
+import kernel.StudiedSystem;
+
+/**
+ * The Class BadContextManager.
+ */
+public class F_XY_System implements StudiedSystem {
+
+ /** The x. */
+ double x = 0;
+ /** The y. */
+ double y = 0;
+ /** The result. */
+ double result = 0;
+ /** The first step. */
+ boolean firstStep = true;
+ double spaceSize;
+ Random generator;
+
+ public F_XY_System(double size) {
+ this.spaceSize = size;
+ }
+
+ private double getResult(double x, double y) {
+ return (y > -spaceSize && y < spaceSize && x < spaceSize && x > -spaceSize) ? 2 * x + y : 5 * x - 8 * y;
+ }
+
+ @Override
+ public void playOneStep() {
+ if (generator == null) {
+ generator = new Random(29);
+ }
+
+ x = (generator.nextDouble() - 0.5) * spaceSize * 4;
+ y = (generator.nextDouble() - 0.5) * spaceSize * 4;
+ }
+
+ @Override
+ public HashMap<String, Double> getOutput() {
+ HashMap<String, Double> out = new HashMap<String, Double>();
+
+ result = getResult(x, y);
+
+ out.put("px0", x);
+ out.put("px1", y);
+ out.put("oracle", 0.0);
+ return out;
+ }
+
+ @Override
+ public double requestOracle(HashMap<String, Double> request) {
+ return getResult(request.get("px"), request.get("py"));
+ }
+
+ @Override
+ public HashMap<String, Double> getOutputWithNoise(double noiseRange) {
+ return null;
+ }
+
+ @Override
+ public HashMap<String, Double> getOutputWithAmoebaRequest(HashMap<String, Double> amoebaRequest,
+ double noiseRange) {
+ return null;
+ }
+
+ @Override
+ public void setActiveLearning(boolean value) {
+ }
+
+ @Override
+ public void setSelfRequest(HashMap<Percept, Double> request) {
+ }
+
+ @Override
+ public HashMap<String, Double> getIntput() {
+ return null;
+ }
}
\ No newline at end of file
diff --git a/AMOEBAonAMAK/src/experiments/MNIST_System.java b/AMOEBAonAMAK/src/experiments/MNIST_System.java
deleted file mode 100644
index eb45954db11b8d1ef57266095279248fcb2a63fc..0000000000000000000000000000000000000000
--- a/AMOEBAonAMAK/src/experiments/MNIST_System.java
+++ /dev/null
@@ -1,225 +0,0 @@
-package experiments;
-
-import java.io.BufferedReader;
-import java.io.File;
-import java.io.FileNotFoundException;
-import java.io.FileReader;
-import java.io.IOException;
-import java.util.ArrayList;
-import java.util.HashMap;
-import java.util.List;
-
-import agents.context.localModel.TypeLocalModel;
-import fr.irit.smac.amak.Configuration;
-import fr.irit.smac.amak.tools.Log;
-import kernel.AMOEBA;
-import kernel.BackupSystem;
-import kernel.IBackupSystem;
-import kernel.StudiedSystem;
-
-/**
- * A system using the MNIST database in the CSV format.
- * You'll need to get it here : https://pjreddie.com/projects/mnist-in-csv/
- */
-public class MNIST_System implements StudiedSystem {
- BufferedReader mnist;
- String path;
- String line;
-
- public MNIST_System(String path) {
- this.path = path;
- try {
- mnist = new BufferedReader(new FileReader(path));
- } catch (FileNotFoundException e) {
- e.printStackTrace();
- System.exit(1);
- }
- }
-
- @Override
- public void playOneStep() {
- try {
- line = mnist.readLine();
- if(line == null) {
- try {
- mnist = new BufferedReader(new FileReader(path));
- } catch (FileNotFoundException e1) {
- e1.printStackTrace();
- System.exit(1);
- }
- playOneStep();
- }
- } catch (IOException e) {
- e.printStackTrace();
- System.err.println("Looping on the file ...");
- try {
- mnist.close();
- mnist = new BufferedReader(new FileReader(path));
- } catch (FileNotFoundException e1) {
- e1.printStackTrace();
- System.exit(1);
- } catch (IOException e1) {
- e1.printStackTrace();
- }
- }
- }
-
- @Override
- public HashMap<String, Double> getOutput() {
- HashMap<String, Double> out = new HashMap<String, Double>();
-
- String[] s = line.split(",");
- for(int i = 1; i < s.length; ++i) {
- out.put(""+i, Double.parseDouble(s[i]));
- }
- out.put("oracle", Double.parseDouble(s[0])*100);
- return out;
- }
-
- /**
- * Evaluate an AMOEBA against a test dataset
- * @param path to the test dataset
- * @param the trained amoeba
- * @param the number of test
- * @return a list with the success rate and the execution time
- */
- public static List<Double> test(String path, AMOEBA amoeba, int nbTests) {
- try {
- long start = 0;
- long end = 0;
- long t = 0;
- BufferedReader test = new BufferedReader(new FileReader(path));
- String line;
- int nb = 0;
- int correct = 0;
- while((line = test.readLine()) != null && nb < nbTests) {
- nb += 1;
- HashMap<String, Double> out = new HashMap<String, Double>();
- String[] s = line.split(",");
- for(int i = 1; i < s.length; ++i) {
- out.put(""+i, Double.parseDouble(s[i]));
- }
- double oracle = Double.parseDouble(s[0]);
- out.put("oracle", oracle*100);
-
- start = System.currentTimeMillis();
- double res = amoeba.request(out);
- end = System.currentTimeMillis();
- t += end-start;
- if(Math.round(res/100) == oracle)
- correct += 1;
- }
- double p = (correct*1.0)/nb;
- //System.out.println(correct+" success on "+nb+" try. "+p);
- test.close();
-
- ArrayList<Double> ret = new ArrayList<>();
- ret.add(p);
- ret.add(t/1000.0);
- return ret;
- } catch (FileNotFoundException e) {
- // TODO Auto-generated catch block
- e.printStackTrace();
- } catch (IOException e) {
- // TODO Auto-generated catch block
- e.printStackTrace();
- }
- return null;
- }
-
- public static void main(String[] args) throws IOException {
- boolean benchmark = true;
- if(benchmark) {
- System.out.println("AMOEBA benchmark with MNIST");
- Log.defaultMinLevel = Log.Level.FATAL;
- Configuration.commandLineMode = true;
-
- File file = new File("resources\\mnist.xml");
-
- // setup cache --- (very important to reduce impact of the 1st measure)
- System.out.println("setup...");
- Configuration.allowedSimultaneousAgentsExecution = 1;
- StudiedSystem learnSystem = new MNIST_System("../../mnist/mnist_train.csv");
- StudiedSystem requestSystem = new MNIST_System("../../mnist/mnist_test.csv");
- AMOEBA amoeba = new AMOEBA();
- amoeba.setLocalModel(TypeLocalModel.AVERAGE);
- IBackupSystem backupSystem = new BackupSystem(amoeba);
- backupSystem.load(file);
- BenchmarkThreading.benchmark(amoeba, learnSystem, requestSystem, 100, 100, 50, null);
- System.out.println("Done. Starting benchmark.");
- // ---------------
- List<List<List<Double>>> results = new ArrayList<>();
- for(int thd = 1; thd <= 8; thd *= 2) {
- Configuration.allowedSimultaneousAgentsExecution = thd;
- learnSystem = new MNIST_System("../../mnist/mnist_train.csv");
- requestSystem = new MNIST_System("../../mnist/mnist_test.csv");
- amoeba = new AMOEBA();
- amoeba.setLocalModel(TypeLocalModel.AVERAGE);
- backupSystem = new BackupSystem(amoeba);
- backupSystem.load(file);
- List<List<Double>> bench = BenchmarkThreading.benchmark(amoeba, learnSystem, requestSystem, 1000, 500, 100, null);
- System.out.println("Thd "+thd+" "+bench);
- results.add(bench);
- }
- String outLearn = "Cycle 1Thd 2Thd 4Thd 8Thd\n";
- String outRequest = "Cycle 1Thd 2Thd 4Thd 8Thd\n";
- for(int i = 0; i < results.get(0).size(); ++i) {
- outLearn += results.get(0).get(i).get(0) +", "+ results.get(0).get(i).get(1) +", "+ results.get(1).get(i).get(1)
- +", "+ results.get(2).get(i).get(1) +", "+ results.get(3).get(i).get(1) +"\n";
- outRequest += results.get(0).get(i).get(0) +", "+ results.get(0).get(i).get(2) +", "+ results.get(1).get(i).get(2)
- +", "+ results.get(2).get(i).get(2) +", "+ results.get(3).get(i).get(2) +"\n";
- }
- System.out.println("Learn : ");
- System.out.println(outLearn);
- System.out.println("Request : ");
- System.out.println(outRequest);
- System.out.println("Done.");
- System.exit(0);
- }
- else {
- System.out.println("To start press a key.");
- System.in.read();
- //Non benchmark usage :
- StudiedSystem studiedSystem = new MNIST_System("..\\..\\mnist\\mnist_train.csv");
- File file = new File("resources\\mnist.xml");
- Configuration.commandLineMode = false;
- Configuration.allowedSimultaneousAgentsExecution = 8;
-
- AMOEBA amoeba = new AMOEBA();
- amoeba.setStudiedSystem(studiedSystem);
- IBackupSystem backupSystem = new BackupSystem(amoeba);
- backupSystem.load(file);
-
- amoeba.setLocalModel(TypeLocalModel.AVERAGE);
-
- //Example for using the learn method
- amoeba.setRenderUpdate(true);
- amoeba.allowGraphicalScheduler(false);
-
- long start = System.currentTimeMillis();
- int nbCycle = 100;
- for(int i = 0; i < nbCycle; ++i) {
- studiedSystem.playOneStep();
- amoeba.learn(studiedSystem.getOutput());
- }
- long end = System.currentTimeMillis();
- System.out.println("Learning done in "+(end-start)/1000.0);
-
- start = System.currentTimeMillis();
- List<Double> ret = test("..\\..\\mnist\\mnist_test.csv", amoeba, 500);
- end = System.currentTimeMillis();
- System.out.println("Accuracy of "+ret.get(0)+" . Done in "+(end-start)/1000.0);
-
- amoeba.setRenderUpdate(true);
- amoeba.allowGraphicalScheduler(true);
-
- System.out.println("End main");
- }
-
- }
-
- @Override
- public double requestOracle(HashMap<String, Double> request) {
- return 0;
- }
-}
\ No newline at end of file
diff --git a/AMOEBAonAMAK/src/experiments/Main.java b/AMOEBAonAMAK/src/experiments/Main.java
index 73ac6686b44a720240b2c3f161457bce23256bb1..4cd5643ea4f16c72567fe716d54b72cd9223787b 100644
--- a/AMOEBAonAMAK/src/experiments/Main.java
+++ b/AMOEBAonAMAK/src/experiments/Main.java
@@ -45,7 +45,6 @@ public class Main {
try {
Thread.currentThread().wait();
} catch (InterruptedException e) {
- // TODO Auto-generated catch block
e.printStackTrace();
}
}
diff --git a/AMOEBAonAMAK/src/experiments/MinimalMain.java b/AMOEBAonAMAK/src/experiments/MinimalMain.java
index 1031fc4301cf767571f65230e5b52c20efb5dbbb..b9b0bde35821831dfe658b762a50be32ceb0540a 100644
--- a/AMOEBAonAMAK/src/experiments/MinimalMain.java
+++ b/AMOEBAonAMAK/src/experiments/MinimalMain.java
@@ -10,12 +10,12 @@ import kernel.StudiedSystem;
*/
public class MinimalMain {
- public static void main(String[] args) {
+ public static void main(String[] args) throws InterruptedException {
// create a system to be studied
- StudiedSystem studiedSystem = new NDimCube(50, 3);
+ StudiedSystem studiedSystem = new F_XY_System(50.0);
// create the amoeba
// Make sure the path to the config file is correct.
- AMOEBA amoeba = new AMOEBA("resources/threeDimensionsLauncher.xml", studiedSystem);
+ AMOEBA amoeba = new AMOEBA("resources/twoDimensionsLauncher.xml", studiedSystem);
// a window should have appeared, allowing you to control and visualize the amoeba.
}
diff --git a/AMOEBAonAMAK/src/experiments/NDimCube.java b/AMOEBAonAMAK/src/experiments/NDimCube.java
index 0b8c8a407ada15c7ed47e0bc0da4f89ead5a2076..fcb7ceb617403a236849ff2f00d7b0b545c27ac3 100644
--- a/AMOEBAonAMAK/src/experiments/NDimCube.java
+++ b/AMOEBAonAMAK/src/experiments/NDimCube.java
@@ -1,105 +1,130 @@
-package experiments;
-
-import java.util.HashMap;
-import java.util.Random;
-
-import fr.irit.smac.amak.tools.Log;
-import kernel.StudiedSystem;
-
-/**
- * System for a N dimension cube.
- */
-public class NDimCube implements StudiedSystem{
-
-
- double[] x ;
- double[] modelCoefs1;
- double[] modelCoefs2;
-
- double result = 0;
- boolean firstStep = true;
- double spaceSize;
- Random generator;
- int dim ;
-
-
- public NDimCube(double size, int dimension) {
- generator = new Random(29);
- this.spaceSize= size;
- this.dim = dimension;
-
- x = new double[dim];
- modelCoefs1 = new double[dim];
- modelCoefs2 = new double[dim];
-
- for(int i = 0; i<dimension; i++) {
- x[i] = 0.0;
-
- modelCoefs1[i] = (int) (Math.random() * 255);
- modelCoefs2[i] = (int) (Math.random() * 255);
- }
-
- String print = "COEFS : ";
- for(int i = 0; i<dimension; i++) {
- print += modelCoefs1[i] + " " + modelCoefs2[i];
- if(i+1 < dimension)
- print += ", ";
- }
- Log.defaultLog.inform("NDimCube", print);
- }
-
- @Override
- public void playOneStep() {
- for(int i = 0; i<dim; i++) {
- x[i] = (generator.nextDouble() - 0.5) * spaceSize * 4;
- }
- }
-
- @Override
- public HashMap<String, Double> getOutput() {
- HashMap<String, Double> out = new HashMap<String, Double>();
-
- for(int i = 0; i<dim; i++) {
-
- if(x[0] > 0) {
- result = getModelResult(1);
- }
- else {
- result = getModelResult(2);
- }
-
- out.put("px" + (i + 1),x[i]);
-
- }
-
- out.put("oracle",result);
- return out;
- }
-
- private double getModelResult(int num) {
- double modelresult = 0.0;
-
- if(num == 1) {
- for(int i=0; i<modelCoefs1.length;i++) {
- modelresult += x[i]*modelCoefs1[i];
- }
- }
- else if(num == 2) {
- for(int i=0; i<modelCoefs2.length;i++) {
- modelresult += x[i]*modelCoefs2[i];
- }
- }
-
- return modelresult;
- }
-
- @Override
- public double requestOracle(HashMap<String, Double> request) {
- if(request.get("px1") > 0) {
- return getModelResult(1);
- }
- else {
- return getModelResult(2);
- }
- }
+package experiments;
+
+import java.util.HashMap;
+import java.util.Random;
+
+import agents.percept.Percept;
+import fr.irit.smac.amak.tools.Log;
+import kernel.StudiedSystem;
+
+/**
+ * System for a N dimension cube.
+ */
+public class NDimCube implements StudiedSystem{
+
+
+ double[] x ;
+ double[] modelCoefs1;
+ double[] modelCoefs2;
+
+ double result = 0;
+ boolean firstStep = true;
+ double spaceSize;
+ Random generator;
+ int dim ;
+
+
+ public NDimCube(double size, int dimension) {
+ generator = new Random(29);
+ this.spaceSize= size;
+ this.dim = dimension;
+
+ x = new double[dim];
+ modelCoefs1 = new double[dim];
+ modelCoefs2 = new double[dim];
+
+ for(int i = 0; i<dimension; i++) {
+ x[i] = 0.0;
+
+ modelCoefs1[i] = (int) (Math.random() * 255);
+ modelCoefs2[i] = (int) (Math.random() * 255);
+ }
+
+ String print = "COEFS : ";
+ for(int i = 0; i<dimension; i++) {
+ print += modelCoefs1[i] + " " + modelCoefs2[i];
+ if(i+1 < dimension)
+ print += ", ";
+ }
+ Log.defaultLog.inform("NDimCube", print);
+ }
+
+ @Override
+ public void playOneStep() {
+ for(int i = 0; i<dim; i++) {
+ x[i] = (generator.nextDouble() - 0.5) * spaceSize * 4;
+ }
+ }
+
+ @Override
+ public HashMap<String, Double> getOutput() {
+ HashMap<String, Double> out = new HashMap<String, Double>();
+
+ for(int i = 0; i<dim; i++) {
+
+ if(x[0] > 0) {
+ result = getModelResult(1);
+ }
+ else {
+ result = getModelResult(2);
+ }
+
+ out.put("px" + (i + 1),x[i]);
+
+ }
+
+ out.put("oracle",result);
+ return out;
+ }
+
+ private double getModelResult(int num) {
+ double modelresult = 0.0;
+
+ if(num == 1) {
+ for(int i=0; i<modelCoefs1.length;i++) {
+ modelresult += x[i]*modelCoefs1[i];
+ }
+ }
+ else if(num == 2) {
+ for(int i=0; i<modelCoefs2.length;i++) {
+ modelresult += x[i]*modelCoefs2[i];
+ }
+ }
+
+ return modelresult;
+ }
+
+ @Override
+ public double requestOracle(HashMap<String, Double> request) {
+ if(request.get("px1") > 0) {
+ return getModelResult(1);
+ }
+ else {
+ return getModelResult(2);
+ }
+ }
+
+ @Override
+ public HashMap<String, Double> getOutputWithNoise(double noiseRange) {
+ return null;
+ }
+
+ @Override
+ public HashMap<String, Double> getOutputWithAmoebaRequest(HashMap<String, Double> amoebaRequest,
+ double noiseRange) {
+ return null;
+ }
+
+ @Override
+ public void setActiveLearning(boolean value) {
+ }
+
+ @Override
+ public void setSelfRequest(HashMap<Percept, Double> request) {
+ }
+
+ @Override
+ public HashMap<String, Double> getIntput() {
+ return null;
+ }
}
\ No newline at end of file
diff --git a/AMOEBAonAMAK/src/experiments/SimpleReinforcement.java b/AMOEBAonAMAK/src/experiments/SimpleReinforcement.java
new file mode 100644
index 0000000000000000000000000000000000000000..85be42842f749fcb26b09c7ae377c9c3a386bf30
--- /dev/null
+++ b/AMOEBAonAMAK/src/experiments/SimpleReinforcement.java
@@ -0,0 +1,169 @@
+package experiments;
+
+import java.io.File;
+import java.io.IOException;
+import java.util.ArrayDeque;
+import java.util.ArrayList;
+import java.util.Deque;
+import java.util.HashMap;
+import java.util.Random;
+
+import fr.irit.smac.amak.Configuration;
+import fr.irit.smac.amak.ui.drawables.Drawable;
+import fr.irit.smac.amak.ui.drawables.DrawableOval;
+import gui.AmoebaWindow;
+import javafx.scene.paint.Color;
+import kernel.AMOEBA;
+import kernel.backup.SaveHelperDummy;
+import utils.Pair;
+import utils.RandomUtils;
+import utils.XmlConfigGenerator;
+
+/**
+ * Train an amoeba on a simple reinforcement task.
+ * The goal of the task is to get to the center. When the position of the agent cross 0, it gets a reward of 100.
+ * The agent can only moves in 2 directions, of a distance of 1. Moving give a reward of -1.
+ * If the agent moves outside of the allowed range, it gets a reward of -100.
+ * @author Hugo
+ *
+ */
+public class SimpleReinforcement {
+
+ private Random rand = new Random();
+ private double x = 0;
+ private double reward = 0;
+ private Drawable pos;
+
+ public static void main(String[] args) {
+ ArrayList<Pair<String, Boolean>> sensors = new ArrayList<>();
+ sensors.add(new Pair<String, Boolean>("p1", false));
+ sensors.add(new Pair<String, Boolean>("a1", true));
+ File config;
+ try {
+ config = File.createTempFile("config", "xml");
+ XmlConfigGenerator.makeXML(config, sensors);
+ } catch (IOException e) {
+ e.printStackTrace();
+ System.exit(1);
+ return; // now compilator know config is initialized
+ }
+
+ Configuration.commandLineMode = true;
+ AMOEBA amoeba = new AMOEBA(config.getAbsolutePath(), null);
+ amoeba.saver = new SaveHelperDummy();
+ SimpleReinforcement env = new SimpleReinforcement();
+
+ Random r = new Random();
+ HashMap<String, Double> state = env.reset();
+ HashMap<String, Double> state2;
+ double explo = 0.5;
+ for(int i = 0; i < 100; i++) {
+ boolean done = false;
+ Deque<HashMap<String, Double>> actions = new ArrayDeque<>();
+ //System.out.println("Explore "+i);
+ int nbStep = 0;
+ state = env.reset();
+ while(!done) {
+ nbStep++;
+ if(nbStep > 500) {
+ done = true;
+ }
+ state.remove("oracle");
+ state.remove("a1");
+ HashMap<String, Double> action = amoeba.maximize(state);
+ if(r.nextDouble() < 0.5 || action.get("oracle").equals(Double.NEGATIVE_INFINITY) ) {
+ //System.out.println("Random action");
+ action.put("a1", (r.nextBoolean() ? 10.0 : -10.0));
+ }
+ state2 = env.step(action.get("a1"));
+
+ if(state2.get("oracle") != -1.0) {
+ done = true;
+ }
+
+ action.put("p1", state.get("p1"));
+ action.put("oracle", state2.get("oracle"));
+ //System.out.println(action);
+ actions.add(action);
+
+ state = state2;
+ }
+
+ //System.out.println("Learn "+i);
+ HashMap<String, Double> action = actions.pop();
+ double reward = action.get("oracle");
+ amoeba.learn(action);
+
+ while(!actions.isEmpty()) {
+ action = actions.pop();
+ reward += action.get("oracle");
+ action.put("oracle", reward);
+ amoeba.learn(action);
+ }
+
+ if(explo > 0.1) {
+ explo -= 0.01;
+ if(explo < 0.1)
+ explo = 0.1;
+ }
+
+ System.out.println("Episode "+i+" reward : "+reward+" explo : "+explo);
+ }
+ }
+
+ /**
+ * Must be called AFTER an AMOEBA with GUI
+ */
+ public SimpleReinforcement() {
+ //Configuration.commandLineMode = false;
+ //AmoebaWindow instance = AmoebaWindow.instance();
+ //pos = new DrawableOval(0.5, 0.5, 1, 1);
+ //pos.setColor(new Color(0.5, 0.0, 0.0, 0.5));
+ //instance.mainVUI.add(pos);
+ //instance.mainVUI.createAndAddRectangle(-50, -0.25, 100, 0.5);
+ //instance.mainVUI.createAndAddRectangle(-0.25, -1, 0.5, 2);
+
+
+
+ }
+
+ public HashMap<String, Double> step(double action){
+ if(action == 0.0) action = rand.nextDouble();
+ if(action > 0.0) action = Math.ceil(action);
+ if(action < 0.0 ) action = Math.floor(action);
+ if(action > 1.0) action = 1.0;
+ if(action < -1.0) action = -1.0;
+ double oldX = x;
+ x = x + action;
+ if(x < -50.0 || x > 50.0) {
+ x = RandomUtils.nextDouble(rand, -50.0, Math.nextUp(50.0));
+ reward = -100.0;
+ } else if(x == 0.0 || sign(oldX) != sign(x)) {
+ // win !
+ reward = 1000.0;
+ x = RandomUtils.nextDouble(rand, -50.0, Math.nextUp(50.0));
+ } else {
+ reward = -1.0;
+ }
+ HashMap<String, Double> ret = new HashMap<>();
+ ret.put("p1", x);
+ ret.put("oracle", reward);
+ //pos.move(x+0.5, 0.5);
+ return ret;
+ }
+
+ public HashMap<String, Double> reset(){
+ x = RandomUtils.nextDouble(rand, -50.0, Math.nextUp(50.0));
+ reward = 0.0;
+
+ HashMap<String, Double> ret = new HashMap<>();
+ ret.put("p1", x);
+ ret.put("oracle", reward);
+ return ret;
+ }
+
+ private int sign(double x) {
+ return x < 0 ? -1 : 1;
+ }
+
+}
diff --git a/AMOEBAonAMAK/src/experiments/TestMain.java b/AMOEBAonAMAK/src/experiments/TestMain.java
new file mode 100644
index 0000000000000000000000000000000000000000..0c1edf926c62fdf0692d299b0789045109b12af0
--- /dev/null
+++ b/AMOEBAonAMAK/src/experiments/TestMain.java
@@ -0,0 +1,247 @@
+package experiments;
+
+import java.util.ArrayList;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.PriorityQueue;
+import java.util.Queue;
+
+import agents.head.EndogenousRequest;
+import fr.irit.smac.amak.tools.Log.Level;
+
+
+
+
+public class TestMain {
+
+
+ public static double fact(double n) {
+
+ if(n==0) {
+ return 1;
+ }
+ else {
+ return n*fact(n-1);
+ }
+ }
+
+ public enum Level {
+ FATAL(60), ERROR(50), IMPORTANT(40), WARNING(30), INFORM(20), DEBUG(10);
+
+ private final int order;
+
+ Level(final int order) {
+ this.order = order;
+ }
+
+ public boolean isGE(final Level _other) {
+ return order >= _other.order;
+ }
+ }
+
+ public static Level minLevel = Level.IMPORTANT;
+
+ private static void trace(final Level _level, final String _message) {
+ if (_level.isGE(minLevel)) {
+ System.out.println(_message);
+ }
+ }
+
+
+
+ public static void main(String[] args) {
+ // TODO Auto-generated method stub
+
+ testLvlTrace();
+
+
+
+ }
+
+ public static void testLvlTrace() {
+ trace(Level.DEBUG, "DEBUG");
+ trace(Level.WARNING, "WARNING");
+ trace(Level.ERROR, "ERROR");
+ trace(Level.FATAL, "FATAL");
+ }
+
+ public static void testPriorityQueue() {
+
+ Queue<EndogenousRequest> endogenousRequest = new PriorityQueue<EndogenousRequest>(new Comparator<EndogenousRequest>(){
+ public int compare(EndogenousRequest r1, EndogenousRequest r2) {
+ return r2.getPriority().compareTo(r1.getPriority());
+ }
+ });
+
+ HashMap<String, Double> hm1 = new HashMap<String, Double>();
+ hm1.put("p1", 50.0);
+ HashMap<String, Double> hm2 = new HashMap<String, Double>();
+ hm2.put("p2", 50.0);
+ HashMap<String, Double> hm3 = new HashMap<String, Double>();
+ hm3.put("p3", 50.0);
+ HashMap<String, Double> hm4 = new HashMap<String, Double>();
+ hm4.put("p4", 50.0);
+ HashMap<String, Double> hm5 = new HashMap<String, Double>();
+ hm5.put("p5", 50.0);
+ HashMap<String, Double> hm6 = new HashMap<String, Double>();
+ hm6.put("p6", 50.0);
+ HashMap<String, Double> hm7 = new HashMap<String, Double>();
+ hm7.put("p7", 50.0);
+// endogenousRequest.add(new EndogenousRequest(hm1, 5));
+// endogenousRequest.add(new EndogenousRequest(hm2, 3));
+// endogenousRequest.add(new EndogenousRequest(hm3, 1));
+// endogenousRequest.add(new EndogenousRequest(hm4, 2));
+// endogenousRequest.add(new EndogenousRequest(hm5, 0));
+// endogenousRequest.add(new EndogenousRequest(hm6, 5));
+// endogenousRequest.add(new EndogenousRequest(hm7, 3));
+
+ System.out.println(endogenousRequest);
+
+ while(endogenousRequest.size()>0){
+ System.out.println(endogenousRequest.poll());
+ }
+ System.out.println(endogenousRequest.poll());
+ }
+
+
+ public static void testBruitGaussien() {
+
+ double noiseVariance = 0.1;
+ double noiseMean = 0;
+
+ double max = 0;
+
+ java.util.Random r = new java.util.Random();
+
+ for(int i =0;i<100000;i++) {
+ double noise = r.nextGaussian() * Math.sqrt(noiseVariance) + noiseMean;
+ System.out.println(noise);
+ if(Math.abs(noise)>max) {
+ max = Math.abs(noise);
+ }
+ }
+
+ System.out.println("-->" + max);
+
+
+
+ }
+
+
+ public static void testCombinaisons() {
+ ArrayList<String> lettres = new ArrayList<String>();
+
+ lettres.add("a");
+ lettres.add("b");
+ lettres.add("c");
+ lettres.add("d");
+ lettres.add("e");
+ lettres.add("f");
+
+ ArrayList<String> combinaisons = new ArrayList<String>();
+
+ int i = 1;
+ for(String lettre : lettres ) {
+
+ for(String otherlettre : lettres.subList(i, lettres.size())) {
+
+ combinaisons.add(lettre + otherlettre);
+
+ }
+ i++;
+
+
+ }
+
+ for(String comb : combinaisons) {
+ System.out.println(comb);
+ }
+ System.out.println(combinaisons.size());
+ System.out.println(fact(lettres.size()) / (2*(fact(lettres.size()-2))));
+ }
+
+ public static void testCompteurTailleN() {
+
+ int[] countIndices = new int[3];
+ int[] bounds = new int[3];
+
+ countIndices[0]=0;
+ countIndices[1]=0;
+ countIndices[2]=0;
+
+ bounds[0]=1;
+ bounds[1]=3;
+ bounds[2]=2;
+
+ boolean test = true;
+
+ int i = 0;
+
+ System.out.println(test + " " + countIndices[0] + " " + countIndices[1] + " " + countIndices[2] );
+
+ while(i<100) {
+
+ test = nextMultiDimCounter(countIndices,bounds);
+
+ System.out.println(test + " " + countIndices[0] + " " + countIndices[1] + " " + countIndices[2] );
+
+ i++;
+ }
+
+ }
+
+ public static boolean nextMultiDimCounter(ArrayList<Integer> indices, ArrayList<Integer> bounds){
+
+
+
+ for(int i = 0; i<indices.size();i++) {
+
+ if(indices.get(i)==bounds.get(i)-1) {
+ if(i==indices.size()-1) {
+ indices.set(i, 0);
+ return false;
+ }
+ else {
+ indices.set(i, 0);
+ }
+ }
+ else {
+ indices.set(i, indices.get(i)+1);
+ return true;
+ }
+
+ }
+
+ return false;
+
+
+ }
+
+ private static boolean nextMultiDimCounter(int[] indices, int[] bounds){
+
+
+
+ for(int i = 0; i<indices.length;i++) {
+
+ if(indices[i]==bounds[i]-1) {
+ if(i==indices.length-1) {
+ indices[i]=0;
+ return false;
+ }
+ else {
+ indices[i]=0;
+ }
+ }
+ else {
+ indices[i] += 1;
+ return true;
+ }
+
+ }
+
+ return false;
+
+
+ }
+
+}
diff --git a/AMOEBAonAMAK/src/experiments/TestingMain.java b/AMOEBAonAMAK/src/experiments/TestingMain.java
new file mode 100644
index 0000000000000000000000000000000000000000..55bfd61be6a785e91185c2cf2eff2c396e810a15
--- /dev/null
+++ b/AMOEBAonAMAK/src/experiments/TestingMain.java
@@ -0,0 +1,76 @@
+package experiments;
+
+import java.util.HashMap;
+
+import fr.irit.smac.amak.Configuration;
+import fr.irit.smac.amak.tools.Log;
+import kernel.AMOEBA;
+import kernel.StudiedSystem;
+import kernel.backup.SaveHelperDummy;
+
+/**
+ * The most minimal main possible producing a functioning amoeba.
+ * @author Hugo
+ *
+ */
+public class TestingMain {
+
+ public static void main(String[] args) throws InterruptedException {
+ Configuration.commandLineMode = false;
+ Log.defaultMinLevel = Log.Level.INFORM;
+ // create a system to be studied
+ StudiedSystem studiedSystem = new NDimCube(50.0, 3);
+ // create the amoeba
+ // Make sure the path to the config file is correct.
+ AMOEBA amoeba = new AMOEBA("resources/threeDimensionsLauncher.xml", studiedSystem);
+ amoeba.saver = new SaveHelperDummy();
+ // a window should have appeared, allowing you to control and visualize the amoeba.
+
+ Thread.sleep(5000);
+
+ long start = System.currentTimeMillis();
+ long end = System.currentTimeMillis();
+ for(int i = 0; i < 1000; i++) {
+ studiedSystem.playOneStep();
+ amoeba.learn(studiedSystem.getOutput());
+ if(i%100 == 99) {
+ end = System.currentTimeMillis();
+ System.out.println("Time for 100 learn: "+(end-start)/1000.0);
+ start = System.currentTimeMillis();
+ }
+ }
+
+ start = System.currentTimeMillis();
+ end = System.currentTimeMillis();
+ for(int i = 0; i < 1000; i++) {
+ studiedSystem.playOneStep();
+ amoeba.request(studiedSystem.getOutput());
+ if(i%100 == 99) {
+ end = System.currentTimeMillis();
+ System.out.println("Time for 100 request: "+(end-start)/1000.0);
+ start = System.currentTimeMillis();
+ }
+ }
+
+ start = System.currentTimeMillis();
+ end = System.currentTimeMillis();
+ for(int i = 0; i < 1000; i++) {
+ studiedSystem.playOneStep();
+ HashMap<String, Double> req = studiedSystem.getOutput();
+ req.remove("px1");
+ req.remove("px2");
+ req.remove("px3");
+ req.remove("oracle");
+ amoeba.maximize(req);
+ if(i%100 == 99) {
+ end = System.currentTimeMillis();
+ System.out.println("Time for 100 maximize: "+(end-start)/1000.0);
+ start = System.currentTimeMillis();
+ }
+ }
+
+ System.exit(0);
+
+ }
+
+}
diff --git a/AMOEBAonAMAK/src/experiments/UnityLauncher/Main.java b/AMOEBAonAMAK/src/experiments/UnityLauncher/Main.java
new file mode 100644
index 0000000000000000000000000000000000000000..099acfb8fc051ddd4d8bdc9e921b199dc79844f7
--- /dev/null
+++ b/AMOEBAonAMAK/src/experiments/UnityLauncher/Main.java
@@ -0,0 +1,259 @@
+package experiments.UnityLauncher;
+
+import java.io.File;
+import java.io.IOException;
+import java.net.ServerSocket;
+import java.net.Socket;
+import java.util.ArrayList;
+
+import agents.context.Context;
+import experiments.FILE;
+import experiments.nDimensionsLaunchers.F_N_Manager;
+import fr.irit.smac.amak.Configuration;
+import gui.AmoebaWindow;
+import kernel.AMOEBA;
+import kernel.StudiedSystem;
+import kernel.backup.BackupSystem;
+import kernel.backup.IBackupSystem;
+import kernel.backup.SaveHelperImpl;
+
+public class Main implements Runnable {
+
+
+
+ public static final double oracleNoiseRange = 0.0;
+ public static final double learningSpeed = 0.01;
+ public static final int regressionPoints = 100;
+ public static final int dimension = 3 ;
+ public static final double spaceSize = 50.0 ;
+ public static final int nbOfModels = 3 ;
+ public static final int normType = 2 ;
+ public static final boolean randomExploration = false;
+ public static final boolean limitedToSpaceZone = true;
+ public static final double mappingErrorAllowed = 0.03;
+ public static final double explorationIncrement = 2.0 ;
+ public static final double explorationWidht = 0.3 ;
+
+ public static final int nbCycle = 10000;
+
+ private SocketServer server;
+
+ /* GUI or not */
+ public static final boolean viewer = false;
+ private String message = "";
+ private Boolean shutDown;
+
+ public Main(ServerSocket ss, Socket s) {
+
+ server = new SocketServer(ss, s);
+ shutDown = false;
+
+ }
+
+ public void run() {
+
+ AmoebaWindow.instance();
+ try {
+ launch();
+ } catch (IOException e) {
+ // TODO Auto-generated catch block
+ e.printStackTrace();
+ }
+
+
+
+
+ }
+
+ public void launch() throws IOException{
+
+
+
+
+ // Set AMAK configuration before creating an AMOEBA
+ Configuration.commandLineMode = false;
+ Configuration.allowedSimultaneousAgentsExecution = 1;
+ Configuration.waitForGUI = true;
+ Configuration.plotMilliSecondsUpdate = 20000;
+
+ AMOEBA amoeba = new AMOEBA();
+ StudiedSystem studiedSystem = new F_N_Manager(spaceSize, dimension, nbOfModels, normType, randomExploration, explorationIncrement,explorationWidht,limitedToSpaceZone, oracleNoiseRange);
+ amoeba.setStudiedSystem(studiedSystem);
+ IBackupSystem backupSystem = new BackupSystem(amoeba);
+ File file = new File("resources/threeDimensionsLauncherUnity.xml");
+ backupSystem.load(file);
+
+
+ amoeba.saver = new SaveHelperImpl(amoeba);
+ amoeba.allowGraphicalScheduler(true);
+ amoeba.setRenderUpdate(true);
+ amoeba.data.learningSpeed = learningSpeed;
+ amoeba.data.numberOfPointsForRegression = regressionPoints;
+ amoeba.getEnvironment().setMappingErrorAllowed(mappingErrorAllowed);
+
+
+ Sender sender = new Sender(server, amoeba);
+
+ studiedSystem.playOneStep();
+ amoeba.learn(studiedSystem.getOutput());
+
+
+
+
+
+ for (int i = 0; i < nbCycle; ++i) {
+
+
+
+
+ studiedSystem.playOneStep();
+ amoeba.learn(studiedSystem.getOutput());
+ if(amoeba.getHeadAgent().isActiveLearning()) {
+
+ studiedSystem.setActiveLearning(true);
+ studiedSystem.setSelfRequest(amoeba.getHeadAgent().getSelfRequest());
+
+ }
+
+
+ ArrayList<Context> spatiallyAlteredContexts = amoeba.getSpatiallyAlteredContextForUnityUI();
+ ArrayList<Context> toKillContexts = amoeba.getToKillContextsForUnityUI();
+
+ if(spatiallyAlteredContexts.size()>0) {
+
+
+
+ sender.sendContexts(spatiallyAlteredContexts);
+
+ while (!sender.acq("CTXTS", amoeba.getCycle())) {
+ try
+ {
+ Thread.sleep(10);
+ }
+ catch(InterruptedException ex)
+ {
+ Thread.currentThread().interrupt();
+ }
+ }
+ }
+
+ if(toKillContexts.size()>0) {
+
+ sender.sendContextsToKill(toKillContexts);
+
+ while (!sender.acq("KILL", amoeba.getCycle())) {
+ try
+ {
+ Thread.sleep(10);
+ }
+ catch(InterruptedException ex)
+ {
+ Thread.currentThread().interrupt();
+ }
+ }
+ }
+ }
+
+
+
+
+
+
+
+ /* AUTOMATIC */
+// long start = System.currentTimeMillis();
+// for (int i = 0; i < nbCycle; ++i) {
+// studiedSystem.playOneStep();
+// amoeba.learn(studiedSystem.getOutput());
+// }
+// long end = System.currentTimeMillis();
+// System.out.println("Done in : " + (end - start) );
+
+
+// /* XP PIERRE */
+//
+// String fileName = fileName(new ArrayList<String>(Arrays.asList("GaussiennePierre")));
+//
+// FILE Pierrefile = new FILE("Pierre",fileName);
+// for (int i = 0; i < nbCycle; ++i) {
+// studiedSystem.playOneStep();
+// amoeba.learn(studiedSystem.getOutput());
+// if(amoeba.getHeadAgent().isActiveLearning()) {
+// studiedSystem.setActiveLearning(true);
+// studiedSystem.setSelfRequest(amoeba.getHeadAgent().getSelfRequest());
+//
+// }
+// }
+//
+// for (int i = 0; i < 10; ++i) {
+// studiedSystem.playOneStep();
+// System.out.println(studiedSystem.getOutput());
+// System.out.println(amoeba.request(studiedSystem.getOutput()));
+//
+//
+// }
+//
+// Pierrefile.write(new ArrayList<String>(Arrays.asList("ID contexte","Coeff Cte","Coeff X0","Coeff X1","Min Value","Max Value")));
+//
+// for(Context ctxt : amoeba.getContexts()) {
+//
+// writeMessage(Pierrefile, ctxt.toStringArrayPierre());
+//
+// }
+//
+//
+// Pierrefile.close();
+
+
+ }
+
+ public static String fileName(ArrayList<String> infos) {
+ String fileName = "";
+
+ for(String info : infos) {
+ fileName += info + "_";
+ }
+
+ return fileName;
+ }
+
+ public static void writeMessage(FILE file, ArrayList<String> message) {
+
+ file.initManualMessage();
+
+ for(String m : message) {
+ file.addManualMessage(m);
+ }
+
+ file.sendManualMessage();
+
+ }
+
+ //////////////////////////////////////////////////////////////////////////////////////////////////
+ //////////////////////////////////////////////////////////////////////////////////////////////////
+
+
+ private void quit(){
+
+ server.close();
+ shutDown = true;
+ }
+
+ private void ack(){
+ //System.out.println("ACK...");
+ //message = readMessage();
+ //System.out.println(message);
+ if(!message.contentEquals("")){
+ server.sendMessage("ACK_" + Integer.toString(server.getMessageCounter()));
+ //System.out.println("ACK");
+ }
+ else{
+ server.sendMessage("ERR_"+Integer.toString(server.getMessageCounter()));
+ }
+ }
+
+
+
+
+}
+
diff --git a/AMOEBAonAMAK/src/experiments/UnityLauncher/Sender.java b/AMOEBAonAMAK/src/experiments/UnityLauncher/Sender.java
new file mode 100644
index 0000000000000000000000000000000000000000..583fd1c3bac535aa98b59aec6820f9b4c81793f0
--- /dev/null
+++ b/AMOEBAonAMAK/src/experiments/UnityLauncher/Sender.java
@@ -0,0 +1,68 @@
+package experiments.UnityLauncher;
+
+import java.util.ArrayList;
+
+import agents.context.Context;
+import agents.percept.Percept;
+import kernel.AMOEBA;
+
+
+
+public class Sender {
+
+ AMOEBA amoeba;
+ SocketServer server;
+
+ public Sender(SocketServer serverInstance,AMOEBA amoebaInstance) {
+ amoeba = amoebaInstance;
+ server = serverInstance;
+ }
+
+ public void sendContexts(ArrayList<Context> contexts) {
+ ArrayList<Percept> percepts = amoeba.getPercepts();
+ String message = initializeMessage("CTXTS");
+
+ for(Context ctxt : contexts) {
+ message += "~";
+ message += ctxt.getName() + "_";
+ message += ctxt.getColorForUnity();
+
+ for(Percept pct : percepts) {
+ message += "_";
+ message += pct.getName() + "#";
+ message += ctxt.getRanges().get(pct).getCenter() + "#";
+ message += ctxt.getRanges().get(pct).getLenght();
+ }
+
+
+ }
+ //System.out.println(message);
+ server.sendMessage(message);
+ }
+
+ public void sendContextsToKill(ArrayList<Context> contexts) {
+ String message = initializeMessage("KILL");
+
+ for(Context ctxt : contexts) {
+ message += "~" + ctxt.getName();
+
+
+ }
+ //System.out.println(message);
+ server.sendMessage(message);
+ }
+
+ private String initializeMessage(String prefix) {
+ return prefix + "~" + amoeba.getCycle();
+ }
+
+ public boolean acq(String type, int cycle) {
+ String message = server.readMessage();
+ String[] tokens = message.split("_");
+ return type.equals(tokens[1]) && Integer.parseInt(tokens[2])==cycle;
+ }
+
+}
+
+
+
diff --git a/AMOEBAonAMAK/src/experiments/UnityLauncher/ServerLauncher.java b/AMOEBAonAMAK/src/experiments/UnityLauncher/ServerLauncher.java
new file mode 100644
index 0000000000000000000000000000000000000000..56d9f2cea541dc58a639425646af78d006319974
--- /dev/null
+++ b/AMOEBAonAMAK/src/experiments/UnityLauncher/ServerLauncher.java
@@ -0,0 +1,31 @@
+package experiments.UnityLauncher;
+
+import java.io.IOException;
+import java.io.Serializable;
+import java.net.ServerSocket;
+import java.net.Socket;
+
+public class ServerLauncher implements Serializable{
+
+ private static ServerSocket socketserver = null;
+ private static Socket socket = null;
+ public static Thread t;
+
+ public static void main(String[] zero) {
+
+ try {
+ socketserver = new ServerSocket(2009);
+ System.out.println("Server ready...");
+ socket = socketserver.accept(); // Un client se connecte on
+ // l'accepte
+ System.out.println("Client connected...");
+ t = new Thread(new Main(socketserver, socket));
+ t.start();
+
+ } catch (IOException e) {
+ System.err.println("Le port " + socket.getLocalPort() + " est d�j� utilis� !");
+ e.printStackTrace();
+ }
+ }
+
+}
diff --git a/AMOEBAonAMAK/src/experiments/UnityLauncher/SocketServer.java b/AMOEBAonAMAK/src/experiments/UnityLauncher/SocketServer.java
new file mode 100644
index 0000000000000000000000000000000000000000..145587d28cb3d00784af81d1acc9109b7adca5f8
--- /dev/null
+++ b/AMOEBAonAMAK/src/experiments/UnityLauncher/SocketServer.java
@@ -0,0 +1,68 @@
+package experiments.UnityLauncher;
+
+import java.io.BufferedReader;
+import java.io.IOException;
+import java.io.InputStreamReader;
+import java.io.PrintWriter;
+import java.net.ServerSocket;
+import java.net.Socket;
+
+public class SocketServer {
+
+ private Socket socket = null;
+ private BufferedReader in = null;
+ private PrintWriter out = null;
+ private int counter;
+
+ public SocketServer(ServerSocket ss, Socket s) {
+ socket = s;
+ counter = 0;
+ }
+
+ public void sendMessage(String message) {
+ try {
+ // socket = socketserver.accept(); // Un client se connecte on
+ // l'accepte
+ out = new PrintWriter(socket.getOutputStream());
+ out.println(message);
+ out.flush();
+ // out.close();
+
+ } catch (IOException e) {
+ System.err.println("D�connection ");
+ }
+
+ }
+
+ public void close(){
+ out.close();
+ }
+
+ public String readMessage() {
+ String message = "";
+ try {
+ // socket = socketserver.accept(); // Un client se connecte on
+ // l'accepte
+ in = new BufferedReader(new InputStreamReader(socket.getInputStream()));
+ message = in.readLine();
+ //System.out.println(message);
+ } catch (IOException e) {
+ System.err.println("Error getOutPut");
+ e.printStackTrace();
+
+ }
+
+ counter ++;
+ //System.out.println("MSG :\t" + message);
+ String delimsTags = "[ _~]+";
+ String[] tokens = message.split(delimsTags);
+
+ return message;
+ }
+
+ public int getMessageCounter(){
+ return counter;
+ }
+
+
+}
diff --git a/AMOEBAonAMAK/src/experiments/nDimensionsLaunchers/F_N_Launcher.java b/AMOEBAonAMAK/src/experiments/nDimensionsLaunchers/F_N_Launcher.java
new file mode 100644
index 0000000000000000000000000000000000000000..ffd17fe59ad4e7b8d2bcd7b5023e7057099d6127
--- /dev/null
+++ b/AMOEBAonAMAK/src/experiments/nDimensionsLaunchers/F_N_Launcher.java
@@ -0,0 +1,174 @@
+package experiments.nDimensionsLaunchers;
+
+import java.io.File;
+import java.io.IOException;
+import java.io.Serializable;
+import java.util.ArrayList;
+
+import experiments.FILE;
+import fr.irit.smac.amak.Configuration;
+import gui.AmoebaWindow;
+import javafx.beans.value.ChangeListener;
+import javafx.beans.value.ObservableValue;
+import javafx.scene.control.Slider;
+import kernel.AMOEBA;
+import kernel.StudiedSystem;
+import kernel.backup.BackupSystem;
+import kernel.backup.IBackupSystem;
+import kernel.backup.SaveHelperImpl;
+
+
+/**
+ * The Class BadContextLauncherEasy.
+ */
+public class F_N_Launcher implements Serializable {
+
+
+ public static final double oracleNoiseRange = 0.5;
+ public static final double learningSpeed = 0.01;
+ public static final int regressionPoints = 100;
+ public static final int dimension = 2;
+ public static final double spaceSize = 50.0 ;
+ public static final int nbOfModels = 3 ;
+ public static final int normType = 2 ;
+ public static final boolean randomExploration = true;
+ public static final boolean limitedToSpaceZone = true;
+ //public static final double mappingErrorAllowed = 0.07; // BIG SQUARE
+ public static double mappingErrorAllowed = 0.03; // MULTI
+ public static final double explorationIncrement = 1.0 ;
+ public static final double explorationWidht = 0.5 ;
+
+ public static final int nbCycle = 1000;
+
+
+
+ public static void main(String[] args) throws IOException {
+ // Instantiating the MainWindow before usage.
+ // It also allows you to change some of its behavior before creating an AMOEBA.
+ // If you use Configuration.commandLineMode = True , then you should skip it.
+ AmoebaWindow.instance();
+ launch();
+ }
+
+
+
+ public static void launch() throws IOException{
+
+
+
+
+ // Set AMAK configuration before creating an AMOEBA
+ Configuration.commandLineMode = false;
+ Configuration.allowedSimultaneousAgentsExecution = 1;
+ Configuration.waitForGUI = true;
+ Configuration.plotMilliSecondsUpdate = 20000;
+
+ AMOEBA amoeba = new AMOEBA();
+ StudiedSystem studiedSystem = new F_N_Manager(spaceSize, dimension, nbOfModels, normType, randomExploration, explorationIncrement,explorationWidht,limitedToSpaceZone, oracleNoiseRange);
+ amoeba.setStudiedSystem(studiedSystem);
+ IBackupSystem backupSystem = new BackupSystem(amoeba);
+ File file = new File("resources/twoDimensionsLauncher.xml");
+ backupSystem.load(file);
+
+ amoeba.saver = new SaveHelperImpl(amoeba);
+ amoeba.allowGraphicalScheduler(true);
+ amoeba.setRenderUpdate(true);
+ amoeba.data.learningSpeed = learningSpeed;
+ amoeba.data.numberOfPointsForRegression = regressionPoints;
+ amoeba.getEnvironment().setMappingErrorAllowed(mappingErrorAllowed);
+
+ // Exemple for adding a tool in the toolbar
+ Slider slider = new Slider(0.01, 0.1, mappingErrorAllowed);
+ slider.setShowTickLabels(true);
+ slider.setShowTickMarks(true);
+
+ slider.valueProperty().addListener(new ChangeListener<Number>() {
+ @Override
+ public void changed(ObservableValue<? extends Number> observable, Number oldValue, Number newValue) {
+ System.out.println("new Value "+newValue);
+ mappingErrorAllowed = (double)newValue;
+ amoeba.getEnvironment().setMappingErrorAllowed(mappingErrorAllowed);
+ }
+ });
+ AmoebaWindow.addToolbar(slider);
+
+ studiedSystem.playOneStep();
+ amoeba.learn(studiedSystem.getOutput());
+
+ /* AUTOMATIC */
+// long start = System.currentTimeMillis();
+// for (int i = 0; i < nbCycle; ++i) {
+// studiedSystem.playOneStep();
+// amoeba.learn(studiedSystem.getOutput());
+// }
+// long end = System.currentTimeMillis();
+// System.out.println("Done in : " + (end - start) );
+//
+// start = System.currentTimeMillis();
+// for (int i = 0; i < nbCycle; ++i) {
+// studiedSystem.playOneStep();
+// amoeba.request(studiedSystem.getOutput());
+// }
+// end = System.currentTimeMillis();
+// System.out.println("Done in : " + (end - start) );
+
+
+// /* XP PIERRE */
+//
+// String fileName = fileName(new ArrayList<String>(Arrays.asList("GaussiennePierre")));
+//
+// FILE Pierrefile = new FILE("Pierre",fileName);
+// for (int i = 0; i < nbCycle; ++i) {
+// studiedSystem.playOneStep();
+// amoeba.learn(studiedSystem.getOutput());
+// if(amoeba.getHeadAgent().isActiveLearning()) {
+// studiedSystem.setActiveLearning(true);
+// studiedSystem.setSelfRequest(amoeba.getHeadAgent().getSelfRequest());
+//
+// }
+// }
+//
+// for (int i = 0; i < 10; ++i) {
+// studiedSystem.playOneStep();
+// System.out.println(studiedSystem.getOutput());
+// System.out.println(amoeba.request(studiedSystem.getOutput()));
+//
+//
+// }
+//
+// Pierrefile.write(new ArrayList<String>(Arrays.asList("ID contexte","Coeff Cte","Coeff X0","Coeff X1","Min Value","Max Value")));
+//
+// for(Context ctxt : amoeba.getContexts()) {
+//
+// writeMessage(Pierrefile, ctxt.toStringArrayPierre());
+//
+// }
+//
+//
+// Pierrefile.close();
+
+
+ }
+
+ public static String fileName(ArrayList<String> infos) {
+ String fileName = "";
+
+ for(String info : infos) {
+ fileName += info + "_";
+ }
+
+ return fileName;
+ }
+
+ public static void writeMessage(FILE file, ArrayList<String> message) {
+
+ file.initManualMessage();
+
+ for(String m : message) {
+ file.addManualMessage(m);
+ }
+
+ file.sendManualMessage();
+
+ }
+}
diff --git a/AMOEBAonAMAK/src/experiments/nDimensionsLaunchers/F_N_Manager.java b/AMOEBAonAMAK/src/experiments/nDimensionsLaunchers/F_N_Manager.java
new file mode 100644
index 0000000000000000000000000000000000000000..a5c51923a19dec1f5678edd58df31573c7561f4f
--- /dev/null
+++ b/AMOEBAonAMAK/src/experiments/nDimensionsLaunchers/F_N_Manager.java
@@ -0,0 +1,705 @@
+package experiments.nDimensionsLaunchers;
+
+import java.io.Serializable;
+import java.util.HashMap;
+import java.util.Random;
+
+import agents.percept.Percept;
+import kernel.StudiedSystem;
+
+
+/**
+ * The Class BadContextManager.
+ */
+public class F_N_Manager implements StudiedSystem{
+
+ /** The x. */
+ Double[] x ;
+
+
+ /** The result. */
+ double result = 0;
+
+ int[] modelCoefs1;
+ int[] modelCoefs2;
+
+ int[][] modelCoefs;
+ double[][] modelCenterZones;
+
+ /** The first step. */
+ boolean firstStep = true;
+ boolean randomExploration = false;
+ boolean spaceLimited = true;
+ double spaceSize;
+
+ int dimension;
+ int numberOfModels;
+ int normType;
+
+ double[] explorationVector;
+
+ HashMap<String,Double> selfRequest;
+ boolean activeLearning = false;
+
+ double noiseRange;
+
+ /** The world. */
+ Random generator;
+
+ double explorationIncrement;
+ double explorationMaxVariation;
+
+
+ /* Parameters */
+ private static final double gaussianCoef = 1000;
+ private static final double gaussianVariance = 10;
+
+
+ public F_N_Manager(double size, int dim, int nbOfModels, int nrmType, boolean rndExploration, double explIncrement, double explnVariation, boolean limiteToSpace, double noise) {
+ this.spaceSize= size;
+ dimension = dim;
+ numberOfModels = nbOfModels;
+ normType = nrmType;
+ x = new Double[dimension];
+
+ noiseRange = noise;
+ spaceLimited = limiteToSpace;
+
+ //gaussianCoef = Math.random()*2000;
+
+ modelCoefs = new int[nbOfModels][dim+1];
+ modelCenterZones = new double[nbOfModels][dim];
+
+
+ for(int nb = 0; nb<nbOfModels; nb++) {
+ for(int i = 0; i<dimension; i++) {
+ x[i] = 0.0;
+
+ modelCoefs[nb][i] = (int) (Math.random() * 500 - 255);
+ modelCenterZones[nb][i] = spaceSize + (Math.random() - 0.5) * spaceSize * 2;
+ }
+ modelCoefs[nb][dimension] = (int) (Math.random() * 500 - 255);
+
+
+ }
+
+ modelCoefs1 = new int[dim+1];
+ modelCoefs2 = new int[dim+1];
+ for(int i = 0; i<dimension; i++) {
+ x[i] = 0.0;
+
+ modelCoefs1[i] = (int) (Math.random() * 500 - 255);
+ modelCoefs2[i] = (int) (Math.random() * 500 - 255);
+ }
+ modelCoefs1[dimension] = (int) (Math.random() * 500 - 255);
+ modelCoefs2[dimension] = (int) (Math.random() * 500 - 255);
+
+
+ System.out.println("ZONE 1 DISKS");
+ for(int nb = 0; nb<nbOfModels; nb++) {
+ System.out.print(modelCoefs[nb][dimension] + "\t");
+ for(int i =0;i<dimension;i++) {
+ System.out.print(modelCoefs[nb][i] + "\t");
+ }
+ System.out.println("");
+ }
+ System.out.println("");
+
+ System.out.println("ZONE 2 MULTIDIM GAUSSIAN");
+ System.out.println(gaussianCoef + " * exp( - ( x +" + spaceSize + ")² / 2 *" + gaussianVariance + "² )");
+ System.out.println("");
+
+ System.out.println("ZONE 3 SQUARE");
+ System.out.print(modelCoefs1[dimension] + "\t");
+ for(int i =0;i<dimension;i++) {
+ System.out.print(modelCoefs1[i] + "\t");
+ }
+ System.out.println("");
+ System.out.print(modelCoefs2[dimension] + "\t");
+ for(int i =0;i<dimension;i++) {
+ System.out.print(modelCoefs2[i] + "\t");
+ }
+ System.out.println("");
+ System.out.println("");
+
+
+
+ randomExploration= rndExploration;
+
+ explorationVector = new double[dimension];
+ for(int i = 0 ; i < dimension ; i++) {
+ explorationVector[i] = Math.random() - 0.5;
+ }
+ double vectorNorm = normeP(explorationVector, 2);
+ for(int i = 0 ; i < dimension ; i++) {
+ explorationVector[i] /= vectorNorm;
+ }
+
+
+ explorationIncrement = explIncrement;
+ explorationMaxVariation = explnVariation;
+ }
+
+
+ /* (non-Javadoc)
+ * @see kernel.StudiedSystem#playOneStep(double)
+ */
+ @Override
+ public void playOneStep() {
+
+
+ if(!randomExploration) {
+
+ nonRandomExplorationStep();
+
+ }
+ else if(activeLearning) {
+
+
+
+ activeLearning = false;
+
+
+
+ for(int i = 0 ; i < dimension ; i++) {
+ x[i] = selfRequest.get("px" + i);
+ }
+ }
+
+ else {
+ if (generator == null) generator = new Random(29);
+
+ for(int i = 0 ; i < dimension ; i++) {
+ x[i] = (generator.nextDouble() - 0.5) * spaceSize * 4;
+ }
+ }
+
+
+ }
+
+
+ private void nonRandomExplorationStep() {
+
+
+ for(int i = 0 ; i < dimension ; i++) {
+ explorationVector[i] += Math.random()*explorationMaxVariation - (explorationMaxVariation/2);
+ }
+ double vectorNorm = normeP(explorationVector, 2);
+ for(int i = 0 ; i < dimension ; i++) {
+ explorationVector[i] /= vectorNorm;
+ }
+
+ for(int i = 0 ; i < dimension ; i++) {
+ x[i] += explorationIncrement*explorationVector[i];
+ if(spaceLimited) {
+ if(x[i]>2*spaceSize) x[i]= -2*spaceSize;
+ if(x[i]<-2*spaceSize) x[i]= 2*spaceSize;
+ }
+
+ }
+
+
+ }
+
+ public void playOneStepConstrained(double[][] constrains) {
+
+ for(int i = 0 ; i < dimension ; i++) {
+ x[i] = constrains[i][0] + (Math.random()*(constrains[i][1] - constrains[i][0]));
+ }
+ }
+
+ public void playOneStepConstrainedWithNoise(double[][] constrains, double noiseRange) {
+
+
+ for(int i = 0 ; i < dimension ; i++) {
+ x[i] = constrains[i][0] + (Math.random()*(constrains[i][1] - constrains[i][0])) - noiseRange/2 + Math.random()*noiseRange;
+ }
+
+ }
+
+
+// public double model() {
+//
+//
+//
+// /* Disc */
+// //return (x[1]*x[1] + x[0]*x[0] < spaceSize*spaceSize ) ? model1() : model2();
+//
+// /* Square */
+// //return (x[1] > -spaceSize && x[1] < spaceSize && x[0] < spaceSize && x[0] > -spaceSize) ? model1() : model2() ;
+// //return model1();
+//
+// /* Triangle */
+// //return (x[1] > x[0]) ? model1() : model2();
+//
+// /* Split */
+// //return ( x <= 0 ) ? 2*x + y : 5*x - 8*y;
+//
+// /* Exp */
+// //return (x[1] > 100*Math.exp(-(Math.pow(x[0]/25, 2))/2) -50) ? model1() : model2();
+//
+//
+// /* Cercle */
+//// double rho = Math.sqrt(x[1]*x[1] + x[0]*x[0]);
+//// double start = 50.0;
+//// double width = 25.0;
+//// return ( (start < rho) && (rho < start + width)) ? model1() : model2();
+//
+//
+// /* Disques */
+// return modelN();
+//
+//
+// /* Gaussian model */
+// //return gaussianModel();
+// }
+
+
+
+
+
+
+ public double model(Double[] situation) {
+
+ Double[] xRequest;
+
+ if(situation == null) {
+ xRequest = x;
+ }else {
+ xRequest = situation;
+ }
+
+ double[] center = new double[2];
+ center[0]=0.0;
+ center[1]=0.0;
+ //return gaussianModel(xRequest, center,gaussianCoef, gaussianVariance);
+ //return squareSimpleModel(xRequest);
+
+ int subzone = subzone2D(xRequest);
+
+ if(subzone == 1) {
+ /* Disques */
+ return modelN(xRequest) ;
+ }else if (subzone == 2) {
+ /* Gaussian model */
+ return gaussianModel(xRequest, subZoneCenter3D(2), gaussianCoef, gaussianVariance);
+
+ }else if (subzone == 3) {
+ /* Square */
+ return square2DModel(xRequest, subZoneCenter3D(3));
+
+ }else if (subzone == 4) {
+ /* Exp */
+ return gaussianMapping2D(xRequest);
+ }
+
+ return model1();
+
+
+ /* Disc */
+ //return (y*y + x*x < spaceSize*spaceSize ) ? 2*x + y : 5*x - 8*y;
+
+ /* Square */
+ //return (x1 > -spaceSize && x1 < spaceSize && x0 < spaceSize && x0 > -spaceSize) ? model1(x0,x1) : model2(x0,x1) ;
+ //return model1();
+
+ /* Triangle */
+ //return (y > x) ? 2*x + y : 5*x - 8*y;
+
+ /* Split */
+ //return ( x <= 0 ) ? 2*x + y : 5*x - 8*y;
+
+
+
+ /* Cercle */
+// double rho = Math.sqrt(x1*x1 + x0*x0);
+// double start = 50.0;
+// double width = 25.0;
+// return ( (start < rho) && (rho < start + width)) ? model1() : model2();
+
+
+
+
+
+ }
+
+
+ private int subzone2D(Double[] situation) {
+
+ Double[] xRequest;
+
+ if(situation == null) {
+ xRequest = x;
+ }else {
+ xRequest = situation;
+ }
+ if(xRequest[0] > 0 && xRequest[1] > 0) {
+ return 1;
+ }else if(xRequest[0] < 0 && xRequest[1] < 0){
+ return 2;
+ }else if(xRequest[0] < 0 && xRequest[1] > 0){
+ return 3;
+ }else if(xRequest[0] > 0 && xRequest[1] < 0){
+ return 4;
+ }else {
+ return 0;
+ }
+
+
+
+ }
+
+ private double[] subZoneCenter2D(int nb) {
+
+ double[] center = new double[2];
+
+ if(nb == 1) {
+ center[0] = spaceSize;
+ center[1] = spaceSize;
+ }else if(nb == 2) {
+ center[0] = -spaceSize;
+ center[1] = -spaceSize;
+ }
+ else if(nb == 3) {
+ center[0] = -spaceSize;
+ center[1] = spaceSize;
+ }
+ else if(nb == 4) {
+ center[0] = spaceSize;
+ center[1] = -spaceSize;
+ }
+
+ return center;
+
+ }
+
+private double[] subZoneCenter3D(int nb) {
+
+ double[] center = new double[3];
+
+ if(nb == 1) {
+ center[0] = spaceSize;
+ center[1] = spaceSize;
+ center[2] = 0.0;
+ }else if(nb == 2) {
+ center[0] = -spaceSize;
+ center[1] = -spaceSize;
+ center[2] = 0.0;
+ }
+ else if(nb == 3) {
+ center[0] = -spaceSize;
+ center[1] = spaceSize;
+ center[2] = 0.0;
+ }
+ else if(nb == 4) {
+ center[0] = spaceSize;
+ center[1] = -spaceSize;
+ center[2] = 0.0;
+ }
+
+ return center;
+
+ }
+
+ private double gaussianMapping2D(Double[] xRequest) {
+ return (xRequest[1] > 30*Math.exp(-(Math.pow((xRequest[0]-spaceSize)/5, 2))/2) -50) ? model1() : model2();
+ }
+
+ private double square2DModel(Double[] xRequest, double[] center) {
+ return ((center[0]-spaceSize/2) < xRequest[0] &&
+ xRequest[0] < (center[0]+spaceSize/2) &&
+ (center[1]-spaceSize/2) < xRequest[1] &&
+ xRequest[1] < (center[1]+spaceSize/2)) ? model1(xRequest[0],xRequest[1]) : model2(xRequest[0],xRequest[1]) ;
+ }
+
+ private double squareSimpleModel(Double[] xRequest) {
+ return ((-spaceSize) < xRequest[0] &&
+ xRequest[0] < (spaceSize) &&
+ (-spaceSize) < xRequest[1] &&
+ xRequest[1] < (+spaceSize)) ? model1(xRequest[0],xRequest[1]) : model2(xRequest[0],xRequest[1]) ;
+ }
+
+ private double gaussianModel() {
+ double result = 1.0;
+ for(int i=0;i<dimension;i++) {
+ result *= Math.exp(-(Math.pow(x[i]/gaussianVariance, 2))/2);
+ }
+ return gaussianCoef*result;
+ }
+
+ private double gaussianModel(Double[] xRequest, double[] center, double factor, double variance) {
+ double result = 1.0;
+ for(int i=0;i<dimension;i++) {
+ result *= Math.exp(-(Math.pow((xRequest[i] - center[i])/variance, 2))/2);
+ }
+ return factor*result;
+ }
+
+ private double modelN() {
+
+ for(int nb = 0; nb<numberOfModels-1; nb++) {
+
+ if(distance(x,modelCenterZones[nb]) < spaceSize) {
+ return modeli(nb);
+ }
+
+ }
+ return modeli(numberOfModels-1);
+
+ }
+
+ private double modelN(Double[] xRequest) {
+
+ for(int nb = 0; nb<numberOfModels-1; nb++) {
+
+ if(distance(xRequest,modelCenterZones[nb]) < spaceSize*0.75) {
+ return modeli(nb, xRequest);
+ }
+
+ }
+ return modeli(numberOfModels-1, xRequest);
+
+ }
+
+ private double distance(Double[] x1, double[] x2) {
+ return normeP(x1,x2,normType);
+ }
+
+ private double norme1(double[] x1, double[] x2) {
+ double distance = 0;
+ for(int i = 0; i < x1.length; i ++) {
+ distance += Math.abs(x2[i] - x1[i]) ;
+ }
+ return distance;
+ }
+
+
+
+ private double normeP(Double[] x1, double[] x2, int p) {
+ double distance = 0;
+ for(int i = 0; i < x1.length; i ++) {
+ distance += Math.pow(Math.abs(x2[i] - x1[i]), p) ;
+ }
+ return Math.pow(distance, 1.0/p);
+ }
+
+ private double normeP(double[] x1, int p) {
+ double distance = 0;
+ for(int i = 0; i < x1.length; i ++) {
+ distance += Math.pow(Math.abs(x1[i]), p) ;
+ }
+ return Math.pow(distance, 1.0/p);
+ }
+
+ private double norme2(double[] x1, double[] x2) {
+ double distance = 0;
+ for(int i = 0; i < x1.length; i ++) {
+ distance += Math.pow(x2[i] - x1[i], 2) ;
+ }
+ return Math.sqrt(distance);
+ }
+
+ private double modeli(int modelNb) {
+ double result = 0.0;
+ for(int i = 0; i<dimension;i++) {
+ result += x[i]*modelCoefs[modelNb][i];
+ }
+ result += modelCoefs[modelNb][dimension];
+ return result;
+ }
+
+ private double modeli(int modelNb, Double[] xRequest) {
+ double result = 0.0;
+ for(int i = 0; i<dimension;i++) {
+ result += xRequest[i]*modelCoefs[modelNb][i];
+ }
+ result += modelCoefs[modelNb][dimension];
+ return result;
+ }
+
+ public double model1() {
+ double result = 0.0;
+ for(int i = 0; i<dimension;i++) {
+ result += x[i]*modelCoefs1[i];
+ }
+ result += modelCoefs1[dimension];
+ return result;
+ }
+
+ public double model2() {
+ double result = 0.0;
+ for(int i = 0; i<dimension;i++) {
+ result += x[i]*modelCoefs2[i];
+ }
+ result += modelCoefs2[dimension];
+ return result;
+ }
+
+ public double model1(double x0, double x1) {
+ double result = 0.0;
+ result += x0*modelCoefs1[0];
+ result += x1*modelCoefs1[1];
+ result += modelCoefs1[dimension];
+ return result;
+ }
+
+ public double model2(double x0, double x1) {
+ double result = 0.0;
+ result += x0*modelCoefs2[0];
+ result += x1*modelCoefs2[1];
+ result += modelCoefs2[dimension];
+ return result;
+ }
+
+ /* (non-Javadoc)
+ * @see kernel.StudiedSystem#getOutput()
+ */
+
+ public HashMap<String, Double> getOutput() {
+ HashMap<String, Double> out = new HashMap<String, Double>();
+
+ result = model(null);
+
+ for(int i = 0; i<dimension; i++) {
+
+ out.put("px" + i,x[i]);
+
+ }
+ out.put("oracle",result);
+ return out;
+ }
+
+ public HashMap<String, Double> getIntput() {
+ HashMap<String, Double> in = new HashMap<String, Double>();
+
+
+ for(int i = 0; i<dimension; i++) {
+
+ in.put("px" + i,x[i]);
+
+ }
+ return in;
+ }
+
+ public HashMap<String, Double> getOutputWithNoise(double noiseRange) {
+ HashMap<String, Double> out = new HashMap<String, Double>();
+
+ result = model(null) - noiseRange/2 + Math.random()*noiseRange ;
+
+ for(int i = 0; i<dimension; i++) {
+
+ out.put("px" + i,x[i]);
+
+ }
+ out.put("oracle",result);
+ return out;
+ }
+
+ public HashMap<String, Double> getOutputWithAmoebaRequest(HashMap<String, Double> amoebaRequest, double noiseRange) {
+ HashMap<String, Double> out = new HashMap<String, Double>();
+
+ for(int i = 0; i<dimension; i++) {
+
+ x[i] = amoebaRequest.get("px" + i);
+
+ }
+
+ result = model(null) - noiseRange/2 + Math.random()*noiseRange ;
+
+ for(int i = 0; i<dimension; i++) {
+
+ out.put("px" + i,x[i]);
+
+ }
+ out.put("oracle",result);
+ return out;
+ }
+
+ public HashMap<String, Double> getOriginOutput() {
+ HashMap<String, Double> out = new HashMap<String, Double>();
+
+ for(int i = 0; i<dimension; i++) {
+ x[i] = 0.0;
+
+ }
+
+ result = model(null);
+
+ for(int i = 0; i<dimension; i++) {
+
+ out.put("px" + i,x[i]);
+
+ }
+ out.put("oracle",result);
+ return out;
+ }
+
+
+
+
+ public HashMap<String, Double> getOutputRequest2D(HashMap<String, Double> values) {
+ HashMap<String, Double> out = new HashMap<String, Double>();
+
+ x[0] = values.get("px0");
+ x[1] = values.get("px1");
+
+
+ result = model(null);
+
+ out.put("px0",x[0]);
+ out.put("px1",x[1]);
+ out.put("oracle",result);
+ return out;
+ }
+
+ /* (non-Javadoc)
+ * @see kernel.StudiedSystem#switchControlMode()
+ */
+
+ public void switchControlMode() {
+
+ }
+
+
+ public double getSpaceSize() {
+ return spaceSize;
+ }
+
+
+
+
+
+
+ @Override
+ public double requestOracle(HashMap<String, Double> request) {
+
+ Double[] xRequest = new Double[request.size()];
+
+ for(int i = 0; i<dimension; i++) {
+
+ xRequest[i] = request.get("px" + i);
+
+ }
+
+ return model(xRequest);
+ }
+
+ @Override
+ public void setActiveLearning(boolean value) {
+ activeLearning = value;
+ }
+
+ @Override
+ public void setSelfRequest(HashMap<Percept, Double> request){
+ HashMap<String,Double> newRequest = new HashMap<String,Double>();
+
+ for(Percept pct : request.keySet()) {
+ newRequest.put(pct.getName(), request.get(pct));
+ }
+
+ selfRequest = newRequest;
+ }
+
+
+
+}
\ No newline at end of file
diff --git a/AMOEBAonAMAK/src/experiments/nDimensionsLaunchers/nDimensionLauncher.xml b/AMOEBAonAMAK/src/experiments/nDimensionsLaunchers/nDimensionLauncher.xml
new file mode 100644
index 0000000000000000000000000000000000000000..53bafe46db4a06ecdc8e41e68e05d4e749953f86
--- /dev/null
+++ b/AMOEBAonAMAK/src/experiments/nDimensionsLaunchers/nDimensionLauncher.xml
@@ -0,0 +1,16 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<System>
+
+ <!-- General config options -->
+ <Configuration>
+ <Learning allowed = "true" creationOfNewContext = "true" loadPresetContext = "false"></Learning>
+ </Configuration>
+
+ <StartingAgents>
+ <Sensor Name="px0" Source="x0"></Sensor>
+ <Sensor Name="px1" Source="x1"></Sensor>
+ <Controller Name="Controller" Oracle="test"></Controller>
+
+ </StartingAgents>
+
+</System>
\ No newline at end of file
diff --git a/AMOEBAonAMAK/src/gui/AmoebaWindow.java b/AMOEBAonAMAK/src/gui/AmoebaWindow.java
index 55aa45af40b1189a1a68edc9f6310d0636b62bf9..ba30d2defb3f74b90dc2e6b45dc9f6c5060b7d80 100644
--- a/AMOEBAonAMAK/src/gui/AmoebaWindow.java
+++ b/AMOEBAonAMAK/src/gui/AmoebaWindow.java
@@ -13,14 +13,18 @@ import fr.irit.smac.amak.ui.SchedulerToolbar;
import fr.irit.smac.amak.ui.VUI;
import fr.irit.smac.amak.ui.drawables.Drawable;
import javafx.application.Application;
+import javafx.beans.value.ChangeListener;
+import javafx.beans.value.ObservableValue;
import javafx.event.ActionEvent;
import javafx.event.EventHandler;
import javafx.scene.control.Button;
import javafx.scene.control.Menu;
+import javafx.scene.control.Slider;
import javafx.scene.control.ToggleButton;
import javafx.scene.control.Tooltip;
+import javafx.scene.paint.Color;
import kernel.AMOEBA;
-import kernel.SaveHelper;
+import kernel.backup.SaveHelperImpl;
/**
* The main window for AMOEBA GUI.
@@ -37,6 +41,7 @@ public class AmoebaWindow extends MainWindow {
public VUI mainVUI;
public Drawable point;
+ public Drawable rectangle;
public ToggleButton toggleRender;
public SchedulerToolbar schedulerToolbar;
public DimensionSelector dimensionSelector;
@@ -59,11 +64,19 @@ public class AmoebaWindow extends MainWindow {
// plots
point = mainVUI.createAndAddPoint(0, 0);
point.setName("Cursor");
+ rectangle = mainVUI.createAndAddRectangle(10, 10, 10, 10);
+ rectangle.setName("Neighborhood");
+ rectangle.setColor(new Color(1, 1, 1, 0));
+
plots.put("This loop NCS", new AmakPlot("This loop NCS", ChartType.LINE, "Cycle", "Number of NCS"));
plots.put("All time NCS", new AmakPlot("All time NCS", ChartType.LINE, "Cycle", "Number of NCS"));
plots.put("Number of agents", new AmakPlot("Number of agents", ChartType.LINE, "Cycle", "Number of agents"));
plots.put("Errors", new AmakPlot("Errors", ChartType.LINE, "Cycle", "Coefficients"));
-
+ plots.put("Distances to models", new AmakPlot("Distances to models", ChartType.LINE, "Cycle", "Distances"));
+ plots.put("Global Mapping Criticality", new AmakPlot("Global Mapping Criticality", ChartType.LINE, "Cycle", "Criticalities"));
+ plots.put("Time Execution", new AmakPlot("Time Execution", ChartType.LINE, "Cycle", "Times"));
+ plots.put("Criticalities", new AmakPlot("Criticalities", ChartType.LINE, "Cycle", "Criticalities"));
+
// update render button
toggleRender = new ToggleButton("Allow Rendering");
toggleRender.setOnAction(evt -> {
@@ -90,6 +103,17 @@ public class AmoebaWindow extends MainWindow {
// manual save button
AmoebaWindow.addToolbar(newManualSaveButton(amoeba));
+
+ Slider slider = new Slider(0, 0.1, 0.1);
+ slider.setShowTickLabels(true);
+ slider.setShowTickMarks(true);
+ slider.valueProperty().addListener(new ChangeListener<Number>() {
+ @Override
+ public void changed(ObservableValue<? extends Number> observable, Number oldValue, Number newValue) {
+ amoeba.getEnvironment().mappingErrorAllowed = newValue.doubleValue();
+ }
+ });
+ AmoebaWindow.addToolbar(slider);
}
/**
@@ -148,7 +172,7 @@ public class AmoebaWindow extends MainWindow {
* @param amoeba
* @return
* @see AMOEBA#saver
- * @see SaveHelper#newManualSave(String)
+ * @see SaveHelperImpl#newManualSave(String)
*/
public Button newManualSaveButton(AMOEBA amoeba) {
Button button = new Button("Quick save");
diff --git a/AMOEBAonAMAK/src/gui/ContextMenuVUI.java b/AMOEBAonAMAK/src/gui/ContextMenuVUI.java
index 44fc782ae2cee1eed356b1532254d56b0eaebfd1..aad5e8bf8af3891878e442f441183af8bd3948f8 100644
--- a/AMOEBAonAMAK/src/gui/ContextMenuVUI.java
+++ b/AMOEBAonAMAK/src/gui/ContextMenuVUI.java
@@ -25,7 +25,10 @@ import kernel.AMOEBA;
*
*/
public class ContextMenuVUI extends ContextMenu {
-
+ /**
+ * If true will skip window asking for input in 2D problems
+ */
+ public static boolean quick2DRequest = false;
private double reqHereX;
private double reqHereY;
@@ -58,7 +61,7 @@ public class ContextMenuVUI extends ContextMenu {
reqHere.setOnAction(new EventHandler<ActionEvent>() {
@Override
public void handle(ActionEvent event) {
- if(amoeba.getPercepts().size() == 2) {
+ if(quick2DRequest && amoeba.getPercepts().size() == 2) {
reqTwoDimension(amoeba, vui);
} else {
reqNDimension(amoeba, vui);
diff --git a/AMOEBAonAMAK/src/gui/ContextRendererFX.java b/AMOEBAonAMAK/src/gui/ContextRendererFX.java
index 0247c37a447a610d727aaf6f6744a52cf908b370..75ddf4125607f21b3ef19ca0dcaaea006105be4d 100644
--- a/AMOEBAonAMAK/src/gui/ContextRendererFX.java
+++ b/AMOEBAonAMAK/src/gui/ContextRendererFX.java
@@ -17,7 +17,7 @@ public class ContextRendererFX extends RenderStrategy {
private Context context;
- private DrawableRectangle drawable;
+ private DrawableContext drawable;
public ContextRendererFX(Object o) {
this((Context) o);
@@ -40,9 +40,14 @@ public class ContextRendererFX extends RenderStrategy {
}
private void updateColor() {
- double[] c = ContextColor.colorFromCoefs(context.getFunction().getCoefs());
+ Double[] c = ContextColor.colorFromCoefs(context.getFunction().getCoef());
drawable.setColor(new Color(c[0], c[1], c[2], 90d / 255d));
}
+
+ public String getColorForUnity() {
+ Double[] c = ContextColor.colorFromCoefs(context.getFunction().getCoef());
+ return c[0].intValue() + "," + c[1].intValue() + "," + c[2].intValue() + ",100";
+ }
private void updatePosition() {
Percept p1 = context.getAmas().getDimensionSelector().d1();
@@ -78,7 +83,7 @@ public class ContextRendererFX extends RenderStrategy {
*/
public DrawableRectangle getDrawable() {
if (!context.isDying() && drawable == null) {
- drawable = new DrawableRectangle(0, 0, 10, 10);
+ drawable = new DrawableContext(0, 0, 0, 0, context);
AmoebaWindow.instance().mainVUI.add(drawable);
}
return drawable;
diff --git a/AMOEBAonAMAK/src/gui/DrawableContext.java b/AMOEBAonAMAK/src/gui/DrawableContext.java
new file mode 100644
index 0000000000000000000000000000000000000000..ab9800c2b0c6cfdb5814115bd8f248d22d312518
--- /dev/null
+++ b/AMOEBAonAMAK/src/gui/DrawableContext.java
@@ -0,0 +1,64 @@
+package gui;
+
+import agents.context.Context;
+import fr.irit.smac.amak.ui.drawables.Drawable;
+import fr.irit.smac.amak.ui.drawables.DrawableDefaultMini;
+import fr.irit.smac.amak.ui.drawables.DrawableRectangle;
+import javafx.geometry.Pos;
+import javafx.scene.control.Button;
+import javafx.scene.layout.HBox;
+
+/**
+ * Drawable for contexts agents, include its mini drawable.
+ * @author Hugo
+ *
+ */
+public class DrawableContext extends DrawableRectangle {
+
+ /**
+ * Mini drawable for context. Add a "destroy" button.
+ * @author Hugo
+ *
+ */
+ public class DrawableContextMini extends DrawableDefaultMini {
+
+ private HBox top;
+
+ public DrawableContextMini(Drawable original, Context context) {
+ super(original);
+
+ top = new HBox();
+ top.setAlignment(Pos.BASELINE_RIGHT);
+ Button destroyButton = new Button("Destroy");
+ destroyButton.setOnAction(e -> {
+ context.destroy();
+ });
+ top.getChildren().add(destroyButton);
+ top.setVisible(false);
+ top.setManaged(false);
+ label.setCenterShape(true);
+ stack.getChildren().add(top);
+ }
+
+ @Override
+ public void expand() {
+ top.setVisible(true);
+ top.setManaged(true);
+ super.expand();
+ }
+
+ @Override
+ public void collapse() {
+ top.setVisible(false);
+ top.setManaged(false);
+ super.collapse();
+ }
+
+ }
+
+ public DrawableContext(double dx, double dy, double width, double height, Context context) {
+ super(dx, dy, width, height);
+ new DrawableContextMini(this, context);
+ }
+
+}
diff --git a/AMOEBAonAMAK/src/gui/saveExplorer/DrawFromXml.java b/AMOEBAonAMAK/src/gui/saveExplorer/DrawFromXml.java
index 3107983389eaf038dfeda92e5161d8c22bbc0ace..d075f06593b1c5c982529305cb5174c2c7d41932 100644
--- a/AMOEBAonAMAK/src/gui/saveExplorer/DrawFromXml.java
+++ b/AMOEBAonAMAK/src/gui/saveExplorer/DrawFromXml.java
@@ -68,7 +68,7 @@ public class DrawFromXml {
}
private static void loadSensor(Element sensorElement, Map<String, Percept> perceptsByName) {
- Percept percept = new Percept(null);
+ Percept percept = new Percept();
percept.setName(sensorElement.getAttributeValue("Name"));
boolean isEnum = Boolean.valueOf(sensorElement.getAttributeValue("Enum"));
percept.setEnum(isEnum);
@@ -187,7 +187,7 @@ public class DrawFromXml {
for(Element e : localModelElement.getChild("Coefs").getChildren()) {
coefs.add(Double.valueOf(e.getAttributeValue("v")));
}
- double[] c = ContextColor.colorFromCoefs(coefs);
+ Double[] c = ContextColor.colorFromCoefs(coefs);
rectangle.setColor(new Color(c[0], c[1], c[2], 90d / 255d));
}
}
diff --git a/AMOEBAonAMAK/src/gui/saveExplorer/SaveExplorer.fxml b/AMOEBAonAMAK/src/gui/saveExplorer/SaveExplorer.fxml
index 3c575f1743927d1491461fa339bde6d526291f64..34fd8894a1f328ebaf5e2384310c3d2878803475 100644
--- a/AMOEBAonAMAK/src/gui/saveExplorer/SaveExplorer.fxml
+++ b/AMOEBAonAMAK/src/gui/saveExplorer/SaveExplorer.fxml
@@ -5,7 +5,6 @@
<?import javafx.scene.control.*?>
<?import javafx.scene.layout.*?>
<?import javafx.scene.layout.VBox?>
-<?import org.kordamp.ikonli.javafx.FontIcon?>
<VBox spacing="5.0" xmlns="http://javafx.com/javafx/8"
xmlns:fx="http://javafx.com/fxml/1"
@@ -21,12 +20,7 @@
<ComboBox fx:id="comboBoxA" />
<HBox alignment="CENTER">
<children>
- <Button mnemonicParsing="false" onAction="#handlePrevA">
- <graphic>
- <FontIcon iconLiteral="dashicons-controls-skipback"
- iconSize="32" />
- </graphic>
- </Button>
+ <Button mnemonicParsing="false" onAction="#handlePrevA" text="<" />
<VBox alignment="CENTER">
<children>
<Button mnemonicParsing="false"
@@ -41,12 +35,7 @@
</HBox>
</children>
</VBox>
- <Button mnemonicParsing="false" onAction="#handleNextA">
- <graphic>
- <FontIcon iconLiteral="dashicons-controls-skipforward"
- iconSize="32" />
- </graphic>
- </Button>
+ <Button mnemonicParsing="false" onAction="#handleNextA" text=">" />
</children>
</HBox>
</children>
@@ -57,12 +46,7 @@
<ComboBox fx:id="comboBoxM" />
<HBox alignment="CENTER">
<children>
- <Button mnemonicParsing="false" onAction="#handlePrevM">
- <graphic>
- <FontIcon iconLiteral="dashicons-controls-skipback"
- iconSize="32" />
- </graphic>
- </Button>
+ <Button mnemonicParsing="false" onAction="#handlePrevM" text="<" />
<VBox alignment="CENTER">
<children>
<Button mnemonicParsing="false"
@@ -77,12 +61,7 @@
</HBox>
</children>
</VBox>
- <Button mnemonicParsing="false" onAction="#handleNextM">
- <graphic>
- <FontIcon iconLiteral="dashicons-controls-skipforward"
- iconSize="32" />
- </graphic>
- </Button>
+ <Button mnemonicParsing="false" onAction="#handleNextM" text=">" />
</children>
</HBox>
</children>
diff --git a/AMOEBAonAMAK/src/gui/saveExplorer/SaveExplorer.java b/AMOEBAonAMAK/src/gui/saveExplorer/SaveExplorer.java
index ff86f8428d54e669719cc362f7e3914162f89a1f..1cb91054d89b371ffccabf2fc05bc2551eab408c 100644
--- a/AMOEBAonAMAK/src/gui/saveExplorer/SaveExplorer.java
+++ b/AMOEBAonAMAK/src/gui/saveExplorer/SaveExplorer.java
@@ -2,6 +2,8 @@ package gui.saveExplorer;
import java.io.File;
import java.io.IOException;
+import java.net.URI;
+import java.net.URL;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.Comparator;
@@ -24,12 +26,12 @@ import javafx.scene.layout.Priority;
import javafx.scene.layout.VBox;
import javafx.util.Callback;
import kernel.AMOEBA;
-import kernel.SaveHelper;
import kernel.StudiedSystem;
+import kernel.backup.SaveHelperImpl;
/**
* Graphical element to browse and load (auto)saves for a specific amoeba.
- * @see SaveHelper
+ * @see SaveHelperImpl
* @see AMOEBA
* @author Hugo
*
@@ -45,13 +47,14 @@ public class SaveExplorer extends VBox {
* create a SaveExplorer for an AMOEBA.
* The amoeba MUST have a working {@link AMOEBA#saver}.
* @param amoeba
- * @see SaveHelper
+ * @see SaveHelperImpl
*/
public SaveExplorer(AMOEBA amoeba) {
this.amoeba = amoeba;
try {
//load the fxml for THIS SaveExplorer
- VBox root = FXMLLoader.load(getClass().getResource("SaveExplorer.fxml"), null, null, new Callback<Class<?>, Object>() {
+ URL url = getClass().getResource("SaveExplorer.fxml");
+ VBox root = FXMLLoader.load(url, null, null, new Callback<Class<?>, Object>() {
@Override
public Object call(Class<?> param) {
return SaveExplorer.this;
@@ -255,7 +258,6 @@ public class SaveExplorer extends VBox {
public static void main(String[] args) throws ClassNotFoundException, IOException {
System.out.println("New AMOEBA launched.");
AMOEBA amoeba = new AMOEBA(args[0], (StudiedSystem)SerializeBase64.deserialize(args[1]));
- amoeba.saver.deleteFolderOnClose = false;
//amoeba.allowGraphicalScheduler(false);
for(Percept p : amoeba.getPercepts()) {
p.setValue(amoeba.getPerceptions(p.getName()));
diff --git a/AMOEBAonAMAK/src/gui/utils/ContextColor.java b/AMOEBAonAMAK/src/gui/utils/ContextColor.java
index b8d3b728c8d790465ed95b1fa40a40996d9830cd..b58fe9d39a5eb0e7de0496b0afe2812d25003018 100644
--- a/AMOEBAonAMAK/src/gui/utils/ContextColor.java
+++ b/AMOEBAonAMAK/src/gui/utils/ContextColor.java
@@ -18,7 +18,7 @@ public class ContextColor {
* @param coefs
* @return
*/
- public static double[] colorFromCoefs(double[] coefs) {
+ public static Double[] colorFromCoefs(Double[] coefs) {
ArrayList<Double> c = new ArrayList<Double>();
for(double v : coefs)
c.add(v);
@@ -30,50 +30,59 @@ public class ContextColor {
* @param coefs
* @return
*/
- public static double[] colorFromCoefs(List<Double> coefs) {
+ public static Double[] colorFromCoefs(List<Double> coefs) {
+ double upperBound = 255;
+ double dispersion = 100;
+
+
Double r = 0.0;
Double g = 0.0;
Double b = 0.0;
- if (coefs.size() > 0) {
- if (coefs.size() == 1) {
- b = normalizePositiveValues(255, 5, Math.abs(coefs.get(0)));
- if (b.isNaN())
- b = 0.0;
- } else if (coefs.size() == 0) {
- g = normalizePositiveValues(255, 5, Math.abs(coefs.get(0)));
- b = normalizePositiveValues(255, 5, Math.abs(coefs.get(1)));
- if (g.isNaN())
- g = 0.0;
- if (b.isNaN())
- b = 0.0;
- } else if (coefs.size() >= 3) {
- r = normalizePositiveValues(255, 5, Math.abs(coefs.get(0)));
- g = normalizePositiveValues(255, 5, Math.abs(coefs.get(1)));
- b = normalizePositiveValues(255, 5, Math.abs(coefs.get(2)));
- if (r.isNaN())
- r = 0.0;
- if (g.isNaN())
- g = 0.0;
- if (b.isNaN())
- b = 0.0;
- } else {
+
+
+ if(coefs.size()>=3) {
+ r = normalizePositiveValues(upperBound, dispersion, Math.abs(coefs.get(0)));
+ g = normalizePositiveValues(upperBound, dispersion, Math.abs(coefs.get(1)));
+ b = normalizePositiveValues(upperBound, dispersion, Math.abs(coefs.get(2)));
+
+ if(r.isNaN() || g.isNaN() || b.isNaN()) {
+ r = 255.0;
+ g = 0.0;
+ b = 0.0;
+ }
+ }else if(coefs.size()==2) {
+ r = normalizePositiveValues(upperBound, dispersion, Math.abs(coefs.get(0)));
+ g = normalizePositiveValues(upperBound, dispersion, Math.abs(coefs.get(1)));
+
+ if(r.isNaN() || g.isNaN() || b.isNaN()) {
+ r = 255.0;
+ g = 0.0;
+ }
+ }else if(coefs.size()==1) {
+ r = normalizePositiveValues(upperBound, dispersion, Math.abs(coefs.get(0)));
+
+ if(r.isNaN() || g.isNaN() || b.isNaN()) {
r = 255.0;
- g = 255.0;
- b = 255.0;
}
- } else {
- r = 255.0;
+ }else {
+ r = 0.0;
g = 255.0;
- b = 255.0;
+ b = 0.0;
}
- double[] ret = new double[3];
+
+
+ Double[] ret = new Double[3];
ret[0] = r / 255.0d;
ret[1] = g / 255.0d;
ret[2] = b / 255.0d;
return ret;
}
+
+
public static double normalizePositiveValues(double upperBound, double dispersion, double value) {
return upperBound * 2 * (-0.5 + 1 / (1 + Math.exp(-value / dispersion)));
}
+
+
}
diff --git a/AMOEBAonAMAK/src/kernel/AMOEBA.java b/AMOEBAonAMAK/src/kernel/AMOEBA.java
index 27f4d55d7bcb459e933dcea2a1f798c71275a2b0..dd2b1e7a6e324d66aac411429f0a847ac00ce42b 100644
--- a/AMOEBAonAMAK/src/kernel/AMOEBA.java
+++ b/AMOEBAonAMAK/src/kernel/AMOEBA.java
@@ -1,561 +1,762 @@
-package kernel;
-
-import java.util.ArrayList;
-import java.util.Collections;
-import java.util.HashMap;
-import java.util.HashSet;
-import java.util.List;
-import java.util.Vector;
-import java.util.concurrent.locks.ReadWriteLock;
-import java.util.concurrent.locks.ReentrantReadWriteLock;
-import java.util.stream.Collectors;
-import java.util.stream.Stream;
-
-import agents.AmoebaAgent;
-import agents.context.Context;
-import agents.context.localModel.LocalModel;
-import agents.context.localModel.LocalModelAverage;
-import agents.context.localModel.LocalModelFirstExp;
-import agents.context.localModel.LocalModelMillerRegression;
-import agents.context.localModel.TypeLocalModel;
-import agents.head.Head;
-import agents.percept.Percept;
-import fr.irit.smac.amak.Agent;
-import fr.irit.smac.amak.Amas;
-import fr.irit.smac.amak.Configuration;
-import fr.irit.smac.amak.Scheduling;
-import fr.irit.smac.amak.tools.Log;
-import fr.irit.smac.amak.tools.RunLaterHelper;
-import fr.irit.smac.amak.ui.AmakPlot;
-import gui.AmoebaWindow;
-import gui.DimensionSelector;
-import ncs.NCS;
-
-/**
- * The AMOEBA amas
- *
- */
-public class AMOEBA extends Amas<World> implements IAMOEBA {
- // -- Attributes
- /**
- * Utility to save, autosave, and load amoebas.
- */
- public SaveHelper saver;
-
- /**
- * The system studied by the amoeba.
- */
- public StudiedSystem studiedSystem;
-
- private Head head;
- private TypeLocalModel localModel = TypeLocalModel.MILLER_REGRESSION;
- private HashMap<String, Double> perceptions = new HashMap<String, Double>();
- private boolean useOracle = true;
-
- private HashSet<Context> validContexts;
- private ReadWriteLock validContextLock = new ReentrantReadWriteLock();
-
- private boolean runAll = false;
- private boolean creationOfNewContext = true;
- private boolean renderUpdate;
-
- private int cycleWithoutRender = 0;
-
- /**
- * Instantiates a new, empty, amoeba.
- * For ease of use, consider using {@link AMOEBA#AMOEBA(String, StudiedSystem)}.
- *
- * @param studiedSystem
- * the studied system
- */
- public AMOEBA() {
- super(new World(), Scheduling.HIDDEN);
- }
-
- /**
- * Intantiate a default amoeba from a config file.
- *
- * @param path path to the config file.
- */
- public AMOEBA(String path, StudiedSystem studiedSystem) {
- super(new World(), Scheduling.HIDDEN);
- this.studiedSystem = studiedSystem;
- setRenderUpdate(true);
- saver = new SaveHelper(this);
- saver.load(path);
- }
-
- @Override
- protected void onInitialConfiguration() {
- }
-
- @Override
- protected void onInitialAgentsCreation() {
- }
-
- @Override
- protected void onRenderingInitialization() {
- AmoebaWindow.instance().initialize(this);
- }
-
- @Override
- protected void onUpdateRender() {
- // Update statistics
- if(AmoebaWindow.isInstance()) {
- AmoebaWindow window = AmoebaWindow.instance();
-
- AmakPlot loopNCS = window.getPlot("This loop NCS");
- AmakPlot allNCS = window.getPlot("All time NCS");
- AmakPlot nbAgent = window.getPlot("Number of agents");
- AmakPlot errors = window.getPlot("Errors");
- boolean notify = isRenderUpdate();
-
- HashMap<NCS, Integer> thisLoopNCS = environment.getThisLoopNCS();
- HashMap<NCS, Integer> allTimeNCS = environment.getAllTimeNCS();
- for (NCS ncs : NCS.values()) {
- loopNCS.addData(ncs, cycle, thisLoopNCS.get(ncs), notify);
- allNCS.addData(ncs, cycle, allTimeNCS.get(ncs), notify);
- }
- nbAgent.addData("Percepts", cycle, getPercepts().size(), notify);
- nbAgent.addData("Contexts", cycle, getContexts().size(), notify);
- nbAgent.addData("Activated", cycle, environment.getNbActivatedAgent(), notify);
-
- errors.addData("Mean criticity", cycle, head.getAveragePredictionCriticity(), notify);
- errors.addData("Error allowed", cycle, head.getErrorAllowed(), notify);
- errors.addData("Inexact allowed", cycle, head.getInexactAllowed(), notify);
- Vector<Double> sortedErrors = new Vector<>(head.getxLastCriticityValues());
- Collections.sort(sortedErrors);
-
- // @note (Labbeti) Test added to avoid crash when head has just been created.
- if (!sortedErrors.isEmpty()) {
- errors.addData("Median criticity", cycle, sortedErrors.get(sortedErrors.size() / 2), notify);
- }
- }
-
- if (isRenderUpdate()) {
- AmoebaWindow.instance().mainVUI.updateCanvas();
- updateAgentsVisualisation();
- RunLaterHelper.runLater(() -> {resetCycleWithoutRender();});
- }
- }
-
- @Override
- protected void onSystemCycleBegin() {
- if (cycle % 1000 == 0) {
- Log.defaultLog.inform("AMOEBA", "Cycle " + cycle);
- }
-
- if(isRenderUpdate()) {
- incrementCycleWithoutRender();
- /* deactivate render update and stop simulation if UI is too far
- * behind the simulation (10 cycles)
- */
- if(getCycleWithoutRender() > 10) {
- setRenderUpdate(false);
- RunLaterHelper.runLater(()->{
- // we (sadly) have to put it inside a runlater to correctly update the slider
- getScheduler().stop();
- });
- Log.defaultLog.warning("AMOEBA UI", "Rendering cannot keep up with simulation, it has been deactivated. "
- + "To reactiavte it, slow down the simulation and toggle the \"Allow Rendering\" button.");
- }
- }
-
- if (studiedSystem != null) {
- studiedSystem.playOneStep();
- perceptions = studiedSystem.getOutput();
- }
- environment.preCycleActions();
- head.clearAllUseableContextLists();
- validContexts = null;
- environment.resetNbActivatedAgent();
- }
-
- synchronized private void incrementCycleWithoutRender() {
- cycleWithoutRender += 1;
- }
-
- synchronized private void resetCycleWithoutRender() {
- cycleWithoutRender = 0;
- }
-
- synchronized private int getCycleWithoutRender() {
- return cycleWithoutRender;
- }
-
- @Override
- protected void onSystemCycleEnd() {
- super.onSystemCycleEnd();
- if(saver != null)
- saver.autosave();
- }
-
- /**
- * Define what is done during a cycle, most importantly it launch agents.
- *
- * Every 1000 cycles, all Context are launched, allowing to delete themselves if
- * they're too small. To change this behavior you have to modify this method.
- */
- @Override
- public void cycle() {
- cycle++;
-
- onSystemCycleBegin();
-
- // run percepts
- List<Percept> synchronousPercepts = getPercepts().stream().filter(a -> a.isSynchronous())
- .collect(Collectors.toList());
- Collections.sort(synchronousPercepts, new AgentOrderComparator());
-
- for (Percept agent : synchronousPercepts) {
- executor.execute(agent);
- }
- try {
- perceptionPhaseSemaphore.acquire(synchronousPercepts.size());
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- try {
- decisionAndActionPhasesSemaphore.acquire(synchronousPercepts.size());
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
-
- // it is sometime useful to run all context agent
- // especially to check if they're not too small,
- // or after reactivating rendering.
- if (cycle % 1000 == 0) {
- runAll = true;
- }
-
- Stream<Context> contextStream = null;
- if (runAll) {
- contextStream = getContexts().stream(); // update all context
- runAll = false;
- } else {
- HashSet<Context> vcontexts = getValidContexts();
- if (vcontexts == null) {
- vcontexts = new HashSet<>();
- }
- contextStream = vcontexts.stream(); // or only valid ones
- }
- // run contexts
- List<Context> synchronousContexts = contextStream.filter(a -> a.isSynchronous()).collect(Collectors.toList());
- Collections.sort(synchronousContexts, new AgentOrderComparator());
-
- for (Context agent : synchronousContexts) {
- executor.execute(agent);
- }
- try {
- perceptionPhaseSemaphore.acquire(synchronousContexts.size());
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- try {
- decisionAndActionPhasesSemaphore.acquire(synchronousContexts.size());
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
-
- // run head
- List<Head> heads = new ArrayList<>();
- heads.add(head);
- List<Head> synchronousHeads = heads.stream().filter(a -> a.isSynchronous()).collect(Collectors.toList());
- Collections.sort(synchronousHeads, new AgentOrderComparator());
-
- for (Head agent : synchronousHeads) {
- executor.execute(agent);
- }
- try {
- perceptionPhaseSemaphore.acquire(synchronousHeads.size());
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- try {
- decisionAndActionPhasesSemaphore.acquire(synchronousHeads.size());
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
-
- removePendingAgents();
-
- addPendingAgents();
-
- onSystemCycleEnd();
-
- if (!Configuration.commandLineMode) {
- onUpdateRender();
-
- if(Configuration.waitForGUI) {
- // we put an action in JavaFX rendering queue
- RunLaterHelper.runLater(() -> {
- renderingPhaseSemaphore.release();
- });
- // and wait for it to finish
- try {
- renderingPhaseSemaphore.acquire();
- } catch (InterruptedException e) {
- Log.defaultLog.error("[AMAS GUI]", "Failed to wait for GUI update to finish.");
- e.printStackTrace();
- }
- // now the queue should be clear
- }
- }
-
- }
-
- @Override
- public void learn(HashMap<String, Double> perceptionsActionState) {
- StudiedSystem ss = studiedSystem;
- studiedSystem = null;
- setPerceptionsAndActionState(perceptionsActionState);
- cycle();
- studiedSystem = ss;
- }
-
- @Override
- public double request(HashMap<String, Double> perceptionsActionState) {
- boolean usingOracle = isUseOracle();
- if (usingOracle)
- head.changeOracleConnection();
- StudiedSystem ss = studiedSystem;
- studiedSystem = null;
- setPerceptionsAndActionState(perceptionsActionState);
- cycle();
- if (usingOracle)
- head.changeOracleConnection();
- studiedSystem = ss;
- return getAction();
- }
-
- public LocalModel buildLocalModel(Context context) {
- if (localModel == TypeLocalModel.MILLER_REGRESSION) {
- return new LocalModelMillerRegression(context.getRanges().size());
- }
- if (localModel == TypeLocalModel.FIRST_EXPERIMENT) {
- return new LocalModelFirstExp();
- }
- if (localModel == TypeLocalModel.AVERAGE) {
- return new LocalModelAverage();
- }
- return null;
- }
-
- /**
- * Activate or deactivate the graphical scheduler. Allowing or denying the user
- * to change the simulation speed.
- *
- * @param allow
- */
- public void allowGraphicalScheduler(boolean allow) {
- if (!Configuration.commandLineMode) {
- AmoebaWindow.instance().schedulerToolbar.setDisable(!allow);
- }
- }
-
- @Override
- public void clearAgents() {
- List<Agent<? extends Amas<World>, World>> agents = getAgents();
- for (Agent<? extends Amas<World>, World> agent : agents) {
- AmoebaAgent amoebaAgent = (AmoebaAgent) agent;
- amoebaAgent.destroy();
- }
- this.head = null;
- super.removePendingAgents();
- }
-
- /**
- * Called when a {@link IBackupSystem} has finished loading the amoeba.
- */
- public void onLoadEnded() {
- super.addPendingAgents();
- nextCycleRunAllAgents();
- if(!Configuration.commandLineMode) {
- AmoebaWindow.instance().dimensionSelector.update(getPercepts());
- updateAgentsVisualisation();
- }
- }
-
- @Override
- public void setCreationOfNewContext(boolean creationOfNewContext) {
- this.creationOfNewContext = creationOfNewContext;
- }
-
- @Override
- public void setHead(Head head) {
- this.head = head;
- }
-
- @Override
- public void setLocalModel(TypeLocalModel localModel) {
- this.localModel = localModel;
- }
-
- /**
- * Activate or deactivate rendering of agents at runtime.
- *
- * @param renderUpdate
- */
- public void setRenderUpdate(boolean renderUpdate) {
- if (!Configuration.commandLineMode) {
- this.renderUpdate = renderUpdate;
- AmoebaWindow.instance().toggleRender.setSelected(renderUpdate);
- if(renderUpdate == true)
- nextCycleRunAllAgents();
- }
- }
-
- /**
- * Set input used by percepts and oracle.
- *
- * @param perceptionsAndActions
- */
- public void setPerceptionsAndActionState(HashMap<String, Double> perceptionsAndActions) {
- this.perceptions = perceptionsAndActions;
- }
-
- /**
- * Get the last prediction from the system.
- *
- * @return
- */
- public double getAction() {
- return head.getAction();
- }
-
- public ArrayList<Context> getContexts() {
- ArrayList<Context> contexts = new ArrayList<>();
- for (Agent<? extends Amas<World>, World> agent : getAgents()) {
- if ((agent instanceof Context)) {
- contexts.add((Context) agent);
- }
- }
- return contexts;
- }
-
- public ArrayList<Head> getHeads() {
- ArrayList<Head> heads = new ArrayList<>();
- heads.add(head);
- return heads;
- }
-
- public ArrayList<Percept> getPercepts() {
- ArrayList<Percept> percepts = new ArrayList<>();
- for (Agent<? extends Amas<World>, World> agent : getAgents()) {
- if ((agent instanceof Percept)) {
- percepts.add((Percept) agent);
- }
- }
- return percepts;
- }
-
- /**
- * Update the set of valid context. The update is done with an intersect of the
- * previous and new set.
- *
- * Synchronized with a writeLock.
- * @param validContexts new validContexts set.
- */
- @SuppressWarnings("unchecked")
- public void updateValidContexts(HashSet<Context> validContexts) {
- validContextLock.writeLock().lock();
- if (this.validContexts == null) {
- this.validContexts = (HashSet<Context>) validContexts.clone();
- } else {
- this.validContexts.retainAll(validContexts);
- }
- validContextLock.writeLock().unlock();
- }
-
- /**
- * Return the current set of valid contexts.
- *
- * Synchronized with a readLock.
- *
- * @return
- */
- public HashSet<Context> getValidContexts() {
- HashSet<Context> ret;
- validContextLock.readLock().lock();
- if (validContexts == null) {
- ret = null;
- } else {
- ret = new HashSet<>(validContexts);
- }
- validContextLock.readLock().unlock();
- return ret;
- }
-
- /**
- * Get the value for a perception
- * @param key key of the perception
- * @return the value of the perception
- */
- public Double getPerceptions(String key) {
- return this.perceptions.get(key);
- }
-
- @Override
- public boolean isCreationOfNewContext() {
- return creationOfNewContext;
- }
-
- /**
- * Tell AMOEBA to run all (contexts) agent for the next cycle.
- */
- public void nextCycleRunAllAgents() {
- runAll = true;
- }
-
- /**
- * Is rendering activated ?
- * @return
- */
- public boolean isRenderUpdate() {
- return (!Configuration.commandLineMode) && renderUpdate;
- }
-
- /**
- * Should AMOEBA use the oracle ? If false then AMOEBA will not learn.
- * @return
- */
- public boolean isUseOracle() {
- return useOracle;
- }
-
- /**
- * Ask the agents to update their visualization, and update some UI element related to them.
- */
- public void updateAgentsVisualisation() {
- for(Agent<? extends Amas<World>, World> a : getAgents()) {
- a.onUpdateRender();
- }
- AmoebaWindow.instance().point.move(AmoebaWindow.instance().dimensionSelector.d1().getValue(), AmoebaWindow.instance().dimensionSelector.d2().getValue());
- AmoebaWindow.instance().mainVUI.updateCanvas();
- AmoebaWindow.instance().point.toFront();
- }
-
- /**
- * The tool telling which dimension to display
- * @return
- */
- public DimensionSelector getDimensionSelector() {
- return AmoebaWindow.instance().dimensionSelector;
- }
-
- /**
- * Get the last perception.
- * @return
- */
- public HashMap<String, Double> getPerceptionsAndActionState() {
- return perceptions;
- }
-
- /**
- * Set the studied system that will be used to learn with the internal scheduler.
- * @param studiedSystem
- */
- public void setStudiedSystem(StudiedSystem studiedSystem) {
- this.studiedSystem = studiedSystem;
- }
-}
+package kernel;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.List;
+import java.util.concurrent.locks.ReadWriteLock;
+import java.util.concurrent.locks.ReentrantReadWriteLock;
+import java.util.stream.Collectors;
+import java.util.stream.Stream;
+
+import agents.AmoebaAgent;
+import agents.context.Context;
+import agents.context.localModel.LocalModel;
+import agents.context.localModel.LocalModelMillerRegression;
+import agents.context.localModel.TypeLocalModel;
+import agents.head.Head;
+import agents.percept.Percept;
+import fr.irit.smac.amak.Agent;
+import fr.irit.smac.amak.Amas;
+import fr.irit.smac.amak.Configuration;
+import fr.irit.smac.amak.Scheduling;
+import fr.irit.smac.amak.tools.Log;
+import fr.irit.smac.amak.tools.RunLaterHelper;
+import fr.irit.smac.amak.ui.AmakPlot;
+import gui.AmoebaWindow;
+import gui.DimensionSelector;
+import kernel.backup.IBackupSystem;
+import kernel.backup.ISaveHelper;
+import kernel.backup.SaveHelperDummy;
+import kernel.backup.SaveHelperImpl;
+import ncs.NCS;
+import utils.PrintOnce;
+
+/**
+ * The AMOEBA amas
+ *
+ */
+public class AMOEBA extends Amas<World> implements IAMOEBA {
+ // -- Attributes
+ /**
+ * Utility to save, autosave, and load amoebas.
+ */
+ public ISaveHelper saver = new SaveHelperDummy();
+
+ /**
+ * The system studied by the amoeba.
+ */
+ public StudiedSystem studiedSystem;
+
+ private Head head;
+ private TypeLocalModel localModel = TypeLocalModel.MILLER_REGRESSION;
+ private HashMap<String, Double> perceptions = new HashMap<String, Double>();
+ private boolean useOracle = true;
+
+ private boolean runAll = false;
+ private boolean creationOfNewContext = true;
+ private boolean renderUpdate;
+
+ private int cycleWithoutRender = 0;
+
+ private ArrayList<Context> spatiallyAlteredContext = new ArrayList<>();
+ private ArrayList<Context> toKillContexts = new ArrayList<>();
+
+ private ArrayList<Context> lastModifiedContext = new ArrayList<>();
+
+ private ArrayList<Context> alteredContexts = new ArrayList<>();
+
+ private HashSet<Context> validContexts;
+ private ReadWriteLock validContextLock = new ReentrantReadWriteLock();
+
+ private HashSet<Context> neighborContexts ;
+ private ReadWriteLock neighborContextsLock = new ReentrantReadWriteLock();
+
+ public AmoebaData data;
+ private ArrayList<Percept> percepts;
+
+ /**
+ * Instantiates a new, empty, amoeba.
+ * For ease of use, consider using {@link AMOEBA#AMOEBA(String, StudiedSystem)}.
+ *
+ * @param studiedSystem
+ * the studied system
+ */
+ public AMOEBA() {
+ super(new World(), Scheduling.HIDDEN);
+ }
+
+ /**
+ * Intantiate a default amoeba from a config file.
+ *
+ * @param path path to the config file.
+ */
+ public AMOEBA(String path, StudiedSystem studiedSystem) {
+ super(new World(), Scheduling.HIDDEN);
+ this.studiedSystem = studiedSystem;
+ setRenderUpdate(true);
+ saver = new SaveHelperImpl(this);
+ saver.load(path);
+ }
+
+ @Override
+ protected void onInitialConfiguration() {
+ super.onInitialConfiguration();
+ if(Configuration.allowedSimultaneousAgentsExecution != 1) {
+ PrintOnce.print("Warning ! Multithreading is not currently sopported !\n"
+ + "Please use Configuration.allowedSimultaneousAgentsExecution=1");
+ }
+ getEnvironment().setAmoeba(this);
+ data = new AmoebaData();
+ }
+
+ @Override
+ protected void onRenderingInitialization() {
+ AmoebaWindow.instance().initialize(this);
+ }
+
+ @Override
+ protected void onUpdateRender() {
+ // Update statistics
+ if(AmoebaWindow.isInstance()) {
+ AmoebaWindow window = AmoebaWindow.instance();
+
+ AmakPlot loopNCS = window.getPlot("This loop NCS");
+ AmakPlot allNCS = window.getPlot("All time NCS");
+ AmakPlot nbAgent = window.getPlot("Number of agents");
+ AmakPlot errors = window.getPlot("Errors");
+ AmakPlot distancesToModels = window.getPlot("Distances to models");
+ AmakPlot gloabalMappingCriticality = window.getPlot("Global Mapping Criticality");
+ AmakPlot timeExecution = window.getPlot("Time Execution");
+ AmakPlot criticalities = window.getPlot("Criticalities");
+
+
+ boolean notify = isRenderUpdate();
+
+ HashMap<NCS, Integer> thisLoopNCS = environment.getThisLoopNCS();
+ HashMap<NCS, Integer> allTimeNCS = environment.getAllTimeNCS();
+ for (NCS ncs : NCS.values()) {
+ loopNCS.addData(ncs, cycle, thisLoopNCS.get(ncs), notify);
+ allNCS.addData(ncs, cycle, allTimeNCS.get(ncs), notify);
+ }
+ nbAgent.addData("Percepts", cycle, getPercepts().size(), notify);
+ nbAgent.addData("Contexts", cycle, getContexts().size(), notify);
+ nbAgent.addData("Activated", cycle, environment.getNbActivatedAgent(), notify);
+
+ errors.addData("Criticality", cycle, head.getNormalizedCriticicality(), notify);
+ errors.addData("Mean criticality", cycle, head.getAveragePredictionCriticity(), notify);
+ errors.addData("Error allowed", cycle, head.getErrorAllowed(), notify);
+
+ distancesToModels.addData("Distance to model", cycle, head.getDistanceToRegression(), notify);
+ distancesToModels.addData("Average distance to model", cycle, head.criticalities.getCriticalityMean("distanceToRegression"), notify);
+ distancesToModels.addData("Allowed distance to model", cycle, head.getDistanceToRegressionAllowed(), notify);
+
+ gloabalMappingCriticality.addData("Current Value", cycle, head.getAverageSpatialCriticality(), notify);
+ gloabalMappingCriticality.addData("Zero", cycle, 0.0, notify);
+
+ timeExecution.addData("HeadPlay", cycle, data.executionTimesSums[0], notify);
+ timeExecution.addData("EndogenousPlay", cycle, data.executionTimesSums[1], notify);
+ timeExecution.addData("ContextSelfAnalisis", cycle, data.executionTimesSums[2], notify);
+ timeExecution.addData("IncompetentNCS", cycle, data.executionTimesSums[3], notify);
+ timeExecution.addData("ConcurrenceNCS", cycle, data.executionTimesSums[4], notify);
+ timeExecution.addData("NewContextNCS", cycle, data.executionTimesSums[5], notify);
+ timeExecution.addData("OvermappingNCS", cycle, data.executionTimesSums[6], notify);
+ timeExecution.addData("Other", cycle, data.executionTimesSums[7], notify);
+ timeExecution.addData("BestContextInNeighbors", cycle, data.executionTimesSums[8], notify);
+ timeExecution.addData("CreateContext", cycle, data.executionTimesSums[9], notify);
+ timeExecution.addData("UpdateStatitics", cycle, data.executionTimesSums[10], notify);
+ timeExecution.addData("ChildContext", cycle, data.executionTimesSums[11], notify);
+ timeExecution.addData("PotentialRequest", cycle, data.executionTimesSums[12], notify);
+
+ criticalities.addData("Prediction", cycle, data.evolutionCriticalityPrediction, notify);
+ criticalities.addData("Mapping", cycle, data.evolutionCriticalityMapping, notify);
+ criticalities.addData("Confidence", cycle, data.evolutionCriticalityConfidence, notify);
+ }
+
+ if (isRenderUpdate()) {
+ AmoebaWindow.instance().mainVUI.updateCanvas();
+ updateAgentsVisualisation();
+ RunLaterHelper.runLater(() -> {resetCycleWithoutRender();});
+ }
+ }
+
+ @Override
+ protected void onSystemCycleBegin() {
+ if (cycle % 1000 == 0) {
+ Log.defaultLog.inform("AMOEBA", "Cycle " + cycle + ". Nb agents: "+getAgents().size());
+ }
+
+ if(isRenderUpdate()) {
+ incrementCycleWithoutRender();
+ /* deactivate render update and stop simulation if UI is too far
+ * behind the simulation (10 cycles)
+ */
+ if(getCycleWithoutRender() > 10) {
+ setRenderUpdate(false);
+ RunLaterHelper.runLater(()->{
+ // we (sadly) have to put it inside a runlater to correctly update the slider
+ getScheduler().stop();
+ });
+ Log.defaultLog.warning("AMOEBA UI", "Rendering cannot keep up with simulation, it has been deactivated. "
+ + "To reactiavte it, slow down the simulation and toggle the \"Allow Rendering\" button.");
+ }
+ }
+
+ if (studiedSystem != null) {
+
+ studiedSystem.playOneStep();
+
+ perceptions = studiedSystem.getOutput();
+
+
+ }
+
+ environment.preCycleActions();
+ head.clearAllUseableContextLists();
+ validContexts = null;
+ neighborContexts = null;
+ environment.resetNbActivatedAgent();
+ spatiallyAlteredContext.clear();
+ toKillContexts.clear();
+ lastModifiedContext.clear();
+ alteredContexts.clear();
+ }
+
+ synchronized private void incrementCycleWithoutRender() {
+ cycleWithoutRender += 1;
+ }
+
+ synchronized private void resetCycleWithoutRender() {
+ cycleWithoutRender = 0;
+ }
+
+ synchronized private int getCycleWithoutRender() {
+ return cycleWithoutRender;
+ }
+
+ @Override
+ protected void onSystemCycleEnd() {
+
+ if(studiedSystem != null) {
+ if(head.isActiveLearning()) {
+ studiedSystem.setActiveLearning(true);
+ studiedSystem.setSelfRequest(head.getSelfRequest());
+
+ }
+ }
+
+ super.onSystemCycleEnd();
+ if(saver != null)
+ saver.autosave();
+ }
+
+ /**
+ * Define what is done during a cycle, most importantly it launch agents.
+ *
+ * Every 1000 cycles, all Context are launched, allowing to delete themselves if
+ * they're too small. To change this behavior you have to modify this method.
+ */
+ @Override
+ public void cycle() {
+ cycle++;
+
+ onSystemCycleBegin();
+
+ // run percepts
+ List<Percept> synchronousPercepts = getPercepts().stream().filter(a -> a.isSynchronous())
+ .collect(Collectors.toList());
+ //Collections.sort(synchronousPercepts, new AgentOrderComparator());
+
+ for (Percept agent : synchronousPercepts) {
+ executor.execute(agent);
+ }
+ try {
+ perceptionPhaseSemaphore.acquire(synchronousPercepts.size());
+ } catch (InterruptedException e) {
+ e.printStackTrace();
+ }
+ try {
+ decisionAndActionPhasesSemaphore.acquire(synchronousPercepts.size());
+ } catch (InterruptedException e) {
+ e.printStackTrace();
+ }
+
+ // it is sometime useful to run all context agent
+ // especially to check if they're not too small,
+ // or after reactivating rendering.
+ if (cycle % 1000 == 0) {
+ runAll = true;
+ }
+
+ Stream<Context> contextStream = null;
+ if (runAll) {
+ contextStream = getContexts().stream(); // update all context
+ runAll = false;
+ } else {
+ HashSet<Context> vcontexts = getValidContexts();
+ if (vcontexts == null) {
+ vcontexts = new HashSet<>();
+ }
+ contextStream = vcontexts.stream(); // or only valid ones
+ }
+
+ getHeadAgent().setActivatedNeighborsContexts(new ArrayList<Context>(getNeighborContexts()));
+
+
+ // run contexts
+ List<Context> synchronousContexts = contextStream.filter(a -> a.isSynchronous()).collect(Collectors.toList());
+ //Collections.sort(synchronousContexts, new AgentOrderComparator());
+
+ for (Context agent : synchronousContexts) {
+ executor.execute(agent);
+ }
+ try {
+ perceptionPhaseSemaphore.acquire(synchronousContexts.size());
+ } catch (InterruptedException e) {
+ e.printStackTrace();
+ }
+ try {
+ decisionAndActionPhasesSemaphore.acquire(synchronousContexts.size());
+ } catch (InterruptedException e) {
+ e.printStackTrace();
+ }
+
+ // run head
+ List<Head> heads = new ArrayList<>();
+ heads.add(head);
+ List<Head> synchronousHeads = heads.stream().filter(a -> a.isSynchronous()).collect(Collectors.toList());
+ //Collections.sort(synchronousHeads, new AgentOrderComparator());
+
+ for (Head agent : synchronousHeads) {
+ executor.execute(agent);
+ }
+ try {
+ perceptionPhaseSemaphore.acquire(synchronousHeads.size());
+ } catch (InterruptedException e) {
+ e.printStackTrace();
+ }
+ try {
+ decisionAndActionPhasesSemaphore.acquire(synchronousHeads.size());
+ } catch (InterruptedException e) {
+ e.printStackTrace();
+ }
+
+ removePendingAgents();
+
+ addPendingAgents();
+
+ onSystemCycleEnd();
+
+ if (!Configuration.commandLineMode) {
+ onUpdateRender();
+
+ if(Configuration.waitForGUI) {
+ // we put an action in JavaFX rendering queue
+ RunLaterHelper.runLater(() -> {
+ renderingPhaseSemaphore.release();
+ });
+ // and wait for it to finish
+ try {
+ renderingPhaseSemaphore.acquire();
+ } catch (InterruptedException e) {
+ Log.defaultLog.error("[AMAS GUI]", "Failed to wait for GUI update to finish.");
+ e.printStackTrace();
+ }
+ // now the queue should be clear
+ }
+ }
+
+ }
+
+ @Override
+ public HashMap<String, Double> learn(HashMap<String, Double> perceptionsActionState) {
+ StudiedSystem ss = studiedSystem;
+ studiedSystem = null;
+ setPerceptionsAndActionState(perceptionsActionState);
+ cycle();
+ studiedSystem = ss;
+
+ return null;
+ }
+
+ @Override
+ public double request(HashMap<String, Double> perceptionsActionState) {
+ boolean usingOracle = isUseOracle();
+ if (usingOracle)
+ head.changeOracleConnection();
+ StudiedSystem ss = studiedSystem;
+ studiedSystem = null;
+ setPerceptionsAndActionState(perceptionsActionState);
+ cycle();
+ if (usingOracle)
+ head.changeOracleConnection();
+ studiedSystem = ss;
+ return getAction();
+ }
+
+ @Override
+ public HashMap<String, Double> maximize(HashMap<String, Double> known){
+ ArrayList<Percept> percepts = getPercepts();
+ ArrayList<Percept> unknown = new ArrayList<>(percepts);
+ unknown.removeIf(p ->known.containsKey(p.getName()));
+ //System.out.println("known : "+known.keySet());
+ //System.out.println("unknow : "+unknown);
+ if(unknown.isEmpty()) {
+ return null;
+ }
+
+ //get partially activated context
+ ArrayList<Context> pac = new ArrayList<>();
+ for(Context c : getContexts()) {
+ boolean good = true;
+ for(String p : known.keySet()) {
+ if(!c.getRangeByPerceptName(p).contains2(known.get(p))) {
+ good = false;
+ break;
+ }
+ }
+ if(good) pac.add(c);
+ }
+
+ ArrayList<HashMap<String, Double>> sol = new ArrayList<>();
+ for(Context c : pac) {
+ sol.add(c.getLocalModel().getMaxWithConstraint(known));
+ }
+ HashMap<String, Double> max = new HashMap<>();
+
+ Double maxValue = Double.NEGATIVE_INFINITY;
+ max.put("oracle", maxValue);
+ //find best solution
+ for(HashMap<String, Double> s : sol) {
+ if(s.get("oracle") > maxValue) {
+ maxValue = s.get("oracle");
+ max = s;
+ }
+ }
+ return max;
+ }
+
+ public LocalModel buildLocalModel(Context context) {
+ switch (localModel) {
+ case MILLER_REGRESSION:
+ return new LocalModelMillerRegression(context);
+
+ default:
+ throw new IllegalArgumentException("Unknown model " + localModel + ".");
+ }
+ }
+
+ /**
+ * Activate or deactivate the graphical scheduler. Allowing or denying the user
+ * to change the simulation speed.
+ *
+ * @param allow
+ */
+ public void allowGraphicalScheduler(boolean allow) {
+ if (!Configuration.commandLineMode) {
+ AmoebaWindow.instance().schedulerToolbar.setDisable(!allow);
+ }
+ }
+
+ @Override
+ public void clearAgents() {
+ List<Agent<? extends Amas<World>, World>> agents = getAgents();
+ for (Agent<? extends Amas<World>, World> agent : agents) {
+ AmoebaAgent amoebaAgent = (AmoebaAgent) agent;
+ amoebaAgent.destroy();
+ }
+ this.head = null;
+ super.removePendingAgents();
+ }
+
+ /**
+ * Called when a {@link IBackupSystem} has finished loading the amoeba.
+ */
+ public void onLoadEnded() {
+ super.addPendingAgents();
+ nextCycleRunAllAgents();
+ if(!Configuration.commandLineMode) {
+ AmoebaWindow.instance().dimensionSelector.update(getPercepts());
+ updateAgentsVisualisation();
+ }
+ }
+
+ @Override
+ public void setCreationOfNewContext(boolean creationOfNewContext) {
+ this.creationOfNewContext = creationOfNewContext;
+ }
+
+ @Override
+ public void setHead(Head head) {
+ this.head = head;
+ }
+
+ @Override
+ public void setLocalModel(TypeLocalModel localModel) {
+ this.localModel = localModel;
+ }
+
+ /**
+ * Activate or deactivate rendering of agents at runtime.
+ *
+ * @param renderUpdate
+ */
+ public void setRenderUpdate(boolean renderUpdate) {
+ if (!Configuration.commandLineMode) {
+ this.renderUpdate = renderUpdate;
+ AmoebaWindow.instance().toggleRender.setSelected(renderUpdate);
+ if(renderUpdate == true)
+ nextCycleRunAllAgents();
+ }
+ }
+
+ /**
+ * Set input used by percepts and oracle.
+ *
+ * @param perceptionsAndActions
+ */
+ public void setPerceptionsAndActionState(HashMap<String, Double> perceptionsAndActions) {
+ this.perceptions = perceptionsAndActions;
+ }
+
+ /**
+ * Get the last prediction from the system.
+ *
+ * @return
+ */
+ public double getAction() {
+ return head.getAction();
+ }
+
+ public ArrayList<Context> getContexts() {
+ ArrayList<Context> contexts = new ArrayList<>();
+ for (Agent<? extends Amas<World>, World> agent : getAgents()) {
+ if ((agent instanceof Context)) {
+ contexts.add((Context) agent);
+ }
+ }
+ return contexts;
+ }
+
+ public ArrayList<Head> getHeads() {
+ ArrayList<Head> heads = new ArrayList<>();
+ heads.add(head);
+ return heads;
+ }
+
+ public ArrayList<Percept> getPercepts() {
+ if(percepts == null || percepts.size()==0) {
+ setPercepts();
+ }
+ return percepts;
+ }
+
+ /**
+ * Get the value for a perception
+ * @param key key of the perception
+ * @return the value of the perception
+ */
+ public Double getPerceptions(String key) {
+ return this.perceptions.get(key);
+ }
+
+ @Override
+ public boolean isCreationOfNewContext() {
+ return creationOfNewContext;
+ }
+
+ /**
+ * Tell AMOEBA to run all (contexts) agent for the next cycle.
+ */
+ public void nextCycleRunAllAgents() {
+ runAll = true;
+ }
+
+ /**
+ * Is rendering activated ?
+ * @return
+ */
+ public boolean isRenderUpdate() {
+ return (!Configuration.commandLineMode) && renderUpdate;
+ }
+
+ /**
+ * Should AMOEBA use the oracle ? If false then AMOEBA will not learn.
+ * @return
+ */
+ public boolean isUseOracle() {
+ return useOracle;
+ }
+
+ /**
+ * Ask the agents to update their visualization, and update some UI element related to them.
+ */
+ public void updateAgentsVisualisation() {
+ for(Agent<? extends Amas<World>, World> a : getAgents()) {
+ a.onUpdateRender();
+ }
+ AmoebaWindow.instance().point.move(AmoebaWindow.instance().dimensionSelector.d1().getValue(), AmoebaWindow.instance().dimensionSelector.d2().getValue());
+ AmoebaWindow.instance().rectangle.setHeight(2*getEnvironment().getContextCreationNeighborhood(null, AmoebaWindow.instance().dimensionSelector.d2()));
+ AmoebaWindow.instance().rectangle.setWidth(2*getEnvironment().getContextCreationNeighborhood(null, AmoebaWindow.instance().dimensionSelector.d1()));
+ AmoebaWindow.instance().rectangle.move(AmoebaWindow.instance().dimensionSelector.d1().getValue() - getEnvironment().getContextCreationNeighborhood(null, AmoebaWindow.instance().dimensionSelector.d1()), AmoebaWindow.instance().dimensionSelector.d2().getValue() - getEnvironment().getContextCreationNeighborhood(null, AmoebaWindow.instance().dimensionSelector.d2()));
+ AmoebaWindow.instance().mainVUI.updateCanvas();
+ AmoebaWindow.instance().point.toFront();
+ AmoebaWindow.instance().point.setInfo(getCursorInfo());
+ }
+
+ /**
+ * The tool telling which dimension to display
+ * @return
+ */
+ public DimensionSelector getDimensionSelector() {
+ return AmoebaWindow.instance().dimensionSelector;
+ }
+
+ /**
+ * Get the last perception.
+ * @return
+ */
+ public HashMap<String, Double> getPerceptionsAndActionState() {
+ return perceptions;
+ }
+
+ /**
+ * Set the studied system that will be used to learn with the internal scheduler.
+ * @param studiedSystem
+ */
+ public void setStudiedSystem(StudiedSystem studiedSystem) {
+ this.studiedSystem = studiedSystem;
+ }
+
+ public Head getHeadAgent() {
+ return head;
+ }
+
+ public ArrayList<Context> getSpatiallyAlteredContextForUnityUI() {
+ return spatiallyAlteredContext;
+ }
+
+ public void addSpatiallyAlteredContextForUnityUI(Context ctxt) {
+ if(!ctxt.isFlat())
+ spatiallyAlteredContext.add(ctxt);
+ }
+
+ public ArrayList<Context> getToKillContextsForUnityUI() {
+ return toKillContexts;
+ }
+
+ public void addToKillContextForUnityUI(Context ctxt) {
+ toKillContexts.add(ctxt);
+ }
+
+ public void addLastmodifiedContext(Context context) {
+ if(!lastModifiedContext.contains(context)) {
+ lastModifiedContext.add(context);
+ }
+ }
+
+ public ArrayList<Context> getLastModifiedContexts(){
+ return lastModifiedContext;
+ }
+
+ /**
+ * Adds the altered context.
+ *
+ * @param context the context
+ */
+ public void addAlteredContext(Context context) {
+ alteredContexts.add(context);
+ }
+
+ /**
+ * Return the current set of valid contexts.
+ *
+ * Synchronized with a readLock.
+ *
+ * @return
+ */
+ public HashSet<Context> getValidContexts() {
+ HashSet<Context> ret;
+ validContextLock.readLock().lock();
+ if (validContexts == null) {
+ ret = null;
+ } else {
+ ret = new HashSet<>(validContexts);
+ }
+ validContextLock.readLock().unlock();
+ return ret;
+ }
+
+ /**
+ * Update the set of valid context. The update is done with an intersect of the
+ * previous and new set.
+ *
+ * Synchronized with a writeLock.
+ * @param validContexts new validContexts set.
+ */
+ @SuppressWarnings("unchecked")
+ public void updateNeighborContexts(HashSet<Context> neighborContexts) {
+ neighborContextsLock.writeLock().lock();
+ if (this.neighborContexts == null) {
+ this.neighborContexts = (HashSet<Context>) neighborContexts.clone();
+ } else {
+ this.neighborContexts.retainAll(neighborContexts);
+ }
+ neighborContextsLock.writeLock().unlock();
+ }
+
+ public HashSet<Context> getNeighborContexts() {
+ HashSet<Context> ret;
+ neighborContextsLock.readLock().lock();
+ if (neighborContexts == null) {
+ ret = null;
+ } else {
+ ret = new HashSet<>(neighborContexts);
+ }
+ neighborContextsLock.readLock().unlock();
+ return ret;
+ }
+
+ /**
+ * Update the set of valid context. The update is done with an intersect of the
+ * previous and new set.
+ *
+ * Synchronized with a writeLock.
+ * @param validContexts new validContexts set.
+ */
+ @SuppressWarnings("unchecked")
+ public void updateValidContexts(HashSet<Context> validContexts) {
+ validContextLock.writeLock().lock();
+ if (this.validContexts == null) {
+ this.validContexts = (HashSet<Context>) validContexts.clone();
+ } else {
+ this.validContexts.retainAll(validContexts);
+ }
+ validContextLock.writeLock().unlock();
+ }
+
+ private String getCursorInfo() {
+ String message = "";
+ for(Percept pct : getPercepts()) {
+ message += pct.getName() + "\t" + pct.getValue() +"\t[ " + pct.getMin() +" ; " + pct.getMax() + " ]\n" ;
+ }
+ return message;
+ }
+
+ public void setPercepts() {
+ percepts = new ArrayList<Percept>();
+ for (Agent<? extends Amas<World>, World> agent : getAgents()) {
+ if ((agent instanceof Percept)) {
+ Percept p = (Percept) agent;
+ if(!p.isDying()) {
+ percepts.add(p);
+ }
+ }
+ }
+ }
+
+ public void addPercept(Percept pct) {
+ percepts = null;
+ }
+
+}
diff --git a/AMOEBAonAMAK/src/kernel/AmoebaData.java b/AMOEBAonAMAK/src/kernel/AmoebaData.java
new file mode 100644
index 0000000000000000000000000000000000000000..5f2e57a82c17eef5f047bdf4a699585dd9f6b8a0
--- /dev/null
+++ b/AMOEBAonAMAK/src/kernel/AmoebaData.java
@@ -0,0 +1,83 @@
+package kernel;
+
+import java.io.Serializable;
+import java.util.HashMap;
+
+import agents.head.DynamicPerformance;
+/**
+ * A Plain Old Java Object for storing parameters for the Head. Keep it as simple as possible for ease of serialization.<br/>
+ * Make sure that all member are : public, serializable, and with a default constructor (taking no parameters).
+ * @author Hugo
+ *
+ */
+public class AmoebaData implements Serializable {
+ private static final long serialVersionUID = 1L;
+
+ public int nPropositionsReceived;
+ public int averagePredictionCriticityWeight = 0;
+ public int numberOfCriticityValuesForAverage = 100;
+ public int numberOfCriticityValuesForAverageforVizualisation = 300;
+
+ public Double prediction;
+ public Double endogenousPredictionActivatedContextsOverlaps = 0.0;
+ public Double endogenousPredictionActivatedContextsOverlapsWorstDimInfluence = 0.0;
+ public Double endogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidence = 0.0;
+ public Double endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidence = 0.0;
+ public Double endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolume = 0.0;
+ public Double endogenousPredictionActivatedContextsSharedIncompetence = 0.0;
+ public Double endogenousPredictionNContexts = 0.0;
+ public Double endogenousPredictionNContextsByInfluence = 0.0;
+
+ public double oracleValue;
+ public double oldOracleValue;
+ public double criticity = 0.0;
+ public double distanceToRegression;
+ public double oldCriticity;
+
+ public double spatialGeneralizationScore = 0;
+
+ public boolean noCreation = true;
+ public boolean useOracle = true;
+ public boolean firstContext = false;
+ public boolean newContextWasCreated = false;
+ public boolean contextFromPropositionWasSelected = false;
+
+ public boolean activeLearning = false;
+
+ public HashMap<String, Double> selfRequest;
+
+ public Double maxConfidence;
+ public Double minConfidence;
+
+ public Double maxPrediction = 1.0;
+ public Double minPrediction = Double.POSITIVE_INFINITY;
+
+ public double normalizedCriticality = 0.0;
+
+ // Endogenous feedback
+ public boolean noBestContext;
+
+ public double evolutionCriticalityPrediction = 0.5;
+ public double evolutionCriticalityMapping = 0.5;
+ public double evolutionCriticalityConfidence = 0.5;
+
+ public int currentCriticalityPrediction = 0;
+ public int currentCriticalityMapping = 0;
+ public int currentCriticalityConfidence = 0;
+
+ public double learningSpeed = 0.25;
+ public int numberOfPointsForRegression = 50;
+
+ public boolean contextNotFinished = false;
+
+ public DynamicPerformance predictionPerformance;
+ public DynamicPerformance regressionPerformance;
+ public DynamicPerformance mappingPerformance;
+
+ public double[] executionTimes = new double[20];
+ public double[] executionTimesSums = new double[20];
+
+ public double initRegressionPerformance = 1.0;
+
+ public double averageRegressionPerformanceIndicator;
+}
\ No newline at end of file
diff --git a/AMOEBAonAMAK/src/kernel/IAMOEBA.java b/AMOEBAonAMAK/src/kernel/IAMOEBA.java
index 072f474eb2fa79f505c88c1b4661501073e472b4..69f379a3519642f06cb278dc1fd08ac6a61c99be 100644
--- a/AMOEBAonAMAK/src/kernel/IAMOEBA.java
+++ b/AMOEBAonAMAK/src/kernel/IAMOEBA.java
@@ -1,54 +1,65 @@
-package kernel;
-
-import java.util.HashMap;
-
-import agents.context.localModel.TypeLocalModel;
-import agents.head.Head;
-
-/**
- * An AMOEBA is an autonomous multi-agent system,
- * capable of learning and making prediction
- *
- */
-public interface IAMOEBA {
- /**
- * Remove ALL agents.
- */
- public void clearAgents();
-
- /**
- * Run a learning cycle.
- * @param perceptionsActionState the output of your studied system.
- */
- public void learn(HashMap<String, Double> perceptionsActionState);
-
- /**
- * Run a cycle without learning.
- * @param perceptionsActionState the output of your studied system.
- * @return the result estimated by AMOEBA.
- */
- public double request(HashMap<String, Double> perceptionsActionState);
-
- /**
- * Set the Head agent.
- * @param head
- */
- public void setHead(Head head);
-
- /**
- * Set the type of local model that will be used by newly created context.
- */
- public void setLocalModel(TypeLocalModel localModel);
-
- /**
- * Allow the creation of new context.
- * @param creationOfNewContext
- */
- public void setCreationOfNewContext(boolean creationOfNewContext);
-
- /**
- * If AMOEBA is allowed to create new context.
- * @return
- */
- public boolean isCreationOfNewContext();
-}
+package kernel;
+
+import java.util.HashMap;
+
+import agents.context.localModel.TypeLocalModel;
+import agents.head.Head;
+
+/**
+ * An AMOEBA is an autonomous multi-agent system,
+ * capable of learning and making prediction
+ *
+ */
+public interface IAMOEBA {
+ /**
+ * Remove ALL agents.
+ */
+ public void clearAgents();
+
+ /**
+ * Run a learning cycle.
+ * @param perceptionsActionState the output of your studied system.
+ */
+ public HashMap<String, Double> learn(HashMap<String, Double> perceptionsActionState);
+
+ /**
+ * Run a cycle without learning.
+ * @param perceptionsActionState the output of your studied system.
+ * @return the result estimated by AMOEBA.
+ */
+ public double request(HashMap<String, Double> perceptionsActionState);
+
+ /**
+ * Try to maximize the oracle. <br/>
+ * The result will be inside a context.<br/>
+ * Inputs are percepts whose value is already known, aka constraints.<br/>
+ * If your request constraint all percepts, return null (you should use {@link AMOEBA#request(HashMap)}).
+ * @param known : HasMap of percept name with their value. Can be empty.
+ * @return HashMap of the percepts optimized, with their value.
+ * If a solution is found, the field "oracle" has its value, else "oracle" is at negative infinity.
+ */
+ public HashMap<String, Double> maximize(HashMap<String, Double> known);
+
+ /**
+ * Set the Head agent.
+ * @param head
+ */
+ public void setHead(Head head);
+
+ /**
+ * Set the type of local model that will be used by newly created context.
+ */
+ public void setLocalModel(TypeLocalModel localModel);
+
+ /**
+ * Allow the creation of new context.
+ * @param creationOfNewContext
+ */
+ public void setCreationOfNewContext(boolean creationOfNewContext);
+
+ /**
+ * If AMOEBA is allowed to create new context.
+ * @return
+ */
+ public boolean isCreationOfNewContext();
+}
diff --git a/AMOEBAonAMAK/src/kernel/SITUATION.java b/AMOEBAonAMAK/src/kernel/SITUATION.java
new file mode 100644
index 0000000000000000000000000000000000000000..46f38af74deb95e6667969036072e08859a55b78
--- /dev/null
+++ b/AMOEBAonAMAK/src/kernel/SITUATION.java
@@ -0,0 +1,12 @@
+package kernel;
+
+import java.io.Serializable;
+
+public enum SITUATION implements Serializable {
+
+ LEARN,
+ REQUEST,
+ CONCURENCE,
+ INCOMPETENCE
+
+}
diff --git a/AMOEBAonAMAK/src/kernel/StudiedSystem.java b/AMOEBAonAMAK/src/kernel/StudiedSystem.java
index 2fabcef7c7f021d8c3b1ddfda6e1ee8f1c8d21d6..0def257b257778365c2639fb813e05a9f3fb324d 100644
--- a/AMOEBAonAMAK/src/kernel/StudiedSystem.java
+++ b/AMOEBAonAMAK/src/kernel/StudiedSystem.java
@@ -1,34 +1,44 @@
-package kernel;
-
-import java.io.Serializable;
-import java.util.HashMap;
-
-import agents.percept.Percept;
-
-/**
- * Any system studied by an instance of AMOEBA must implement this interface.
- *
- */
-public interface StudiedSystem extends Serializable{
-
- /**
- * Tell the StudiedSystem to advance its simulation of one step
- */
- public void playOneStep();
-
- /**
- * Gets the output for the current step.
- *
- * @return an {@link HashMap} containing a value for each {@link Percept} of an {@link AMOEBA} and a value for the oracle.
- */
- public HashMap<String, Double> getOutput();
-
- /**
- * Ask the studied system to provide an oracle for a specific input.
- *
- * @param request the input we wish to get an oracle.
- * @return the oracle value.
- */
- public double requestOracle(HashMap<String, Double> request);
-
-}
+package kernel;
+
+import java.io.Serializable;
+import java.util.HashMap;
+
+import agents.percept.Percept;
+
+/**
+ * Any system studied by an instance of AMOEBA must implement this interface.
+ *
+ */
+public interface StudiedSystem extends Serializable{
+
+ /**
+ * Tell the StudiedSystem to advance its simulation of one step
+ */
+ public void playOneStep();
+
+ /**
+ * Gets the output for the current step.
+ *
+ * @return an {@link HashMap} containing a value for each {@link Percept} of an {@link AMOEBA} and a value for the oracle.
+ */
+ public HashMap<String, Double> getOutput();
+ public HashMap<String, Double> getIntput();
+
+ public HashMap<String, Double> getOutputWithNoise(double noiseRange);
+
+ public HashMap<String, Double> getOutputWithAmoebaRequest(HashMap<String, Double> amoebaRequest, double noiseRange);
+
+ /**
+ * Ask the studied system to provide an oracle for a specific input.
+ *
+ * @param request the input we wish to get an oracle.
+ * @return the oracle value.
+ */
+ public double requestOracle(HashMap<String, Double> request);
+
+ public void setActiveLearning(boolean value);
+
+
+ public void setSelfRequest(HashMap<Percept, Double> request);
+
+}
diff --git a/AMOEBAonAMAK/src/kernel/World.java b/AMOEBAonAMAK/src/kernel/World.java
index c7663b68f334a1439611be571092324fe508fd5e..e248a189449055d43fff29bc5ac33ff3d1e90fdf 100644
--- a/AMOEBAonAMAK/src/kernel/World.java
+++ b/AMOEBAonAMAK/src/kernel/World.java
@@ -1,96 +1,149 @@
-package kernel;
-
-import java.util.HashMap;
-
-import fr.irit.smac.amak.Environment;
-import fr.irit.smac.amak.Scheduling;
-import ncs.NCS;
-
-/**
- * Store some data about the world
- *
- */
-public class World extends Environment {
-
- private HashMap<NCS,Integer> numberOfNCS = new HashMap<NCS,Integer>();
- private HashMap<NCS,Integer> allTimeNCS = new HashMap<NCS,Integer>();
- private HashMap<NCS,Integer> thisLoopNCS = new HashMap<NCS,Integer>();
-
- private int nbActivatedAgent;
- private double AVT_acceleration = 2;
- private double AVT_deceleration = 1. / 3.0;
- private double AVT_percentAtStart = 0.2;
-
- /**
- * Instantiates a new world.
- *
- */
- public World() {
- super(Scheduling.HIDDEN);
-
- for (NCS ncs : NCS.values()) {
- numberOfNCS.put(ncs, 0);
- }
-
- for (NCS ncs : NCS.values()) {
- allTimeNCS.put(ncs, 0);
- thisLoopNCS.put(ncs, 0);
- }
- }
-
- public synchronized void raiseNCS(NCS ncs) {
- thisLoopNCS.put(ncs, thisLoopNCS.get(ncs) + 1);
-
- if (ncs.equals(NCS.CONTEXT_CONFLICT_FALSE)
- || ncs.equals(NCS.HEAD_INCOMPETENT)) {
- NCS.a = true;
- }
- }
-
- public void changeNCSNumber(int x, NCS ncs) {
- if (numberOfNCS.containsKey(ncs)) {
- numberOfNCS.put(ncs, numberOfNCS.get(ncs) + x);
- } else {
- numberOfNCS.put(ncs, x);
- }
- }
-
- public double getAVT_acceleration() {
- return AVT_acceleration;
- }
-
- public double getAVT_deceleration() {
- return AVT_deceleration;
- }
-
- public double getAVT_percentAtStart() {
- return AVT_percentAtStart;
- }
-
- public void preCycleActions() {
- for (NCS ncs : NCS.values()) {
- allTimeNCS.put(ncs, allTimeNCS.get(ncs) + thisLoopNCS.get(ncs));
- thisLoopNCS.put(ncs, 0);
- }
- }
-
- public HashMap<NCS, Integer> getThisLoopNCS() {
- return thisLoopNCS;
- }
-
- public HashMap<NCS, Integer> getAllTimeNCS() {
- return allTimeNCS;
- }
-
- public synchronized void incrementNbActivatedAgent() {
- nbActivatedAgent += 1;
- }
-
- public int getNbActivatedAgent() {
- return nbActivatedAgent;
- }
-
- public void resetNbActivatedAgent() {
- nbActivatedAgent = 0;
- }
-}
+package kernel;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+
+import fr.irit.smac.amak.Environment;
+import fr.irit.smac.amak.Scheduling;
+import agents.context.Context;
+import agents.percept.Percept;
+import experiments.TestMain.Level;
+import ncs.NCS;
+import utils.TRACE_LEVEL;
+
+/**
+ * Store some data about the world
+ *
+ */
+public class World extends Environment {
+
+ private HashMap<NCS, Integer> numberOfNCS = new HashMap<NCS, Integer>();
+ private HashMap<NCS, Integer> allTimeNCS = new HashMap<NCS, Integer>();
+ private HashMap<NCS, Integer> thisLoopNCS = new HashMap<NCS, Integer>();
+
+ public double increment_up = 0.05;
+
+ private int nbActivatedAgent;
+ private double AVT_acceleration = 2;
+ private double AVT_deceleration = 1. / 3.0;
+ private double AVT_percentAtStart = 0.2;
+
+ public double mappingErrorAllowed = 0.04;// TODO remove from here --> head agent
+
+ public int regressionPoints = 0; // TODO remove from here
+
+
+
+ public static TRACE_LEVEL minLevel = TRACE_LEVEL.ERROR;
+
+ private AMOEBA amoeba;
+
+ /**
+ * Instantiates a new world.
+ *
+ */
+ public World() {
+ super(Scheduling.HIDDEN);
+
+ for (NCS ncs : NCS.values()) {
+ numberOfNCS.put(ncs, 0);
+ }
+
+ for (NCS ncs : NCS.values()) {
+ allTimeNCS.put(ncs, 0);
+ thisLoopNCS.put(ncs, 0);
+ }
+ }
+
+ public double getMappingErrorAllowed() {
+ return mappingErrorAllowed;
+ }
+
+ public void setMappingErrorAllowed(double value) {
+ mappingErrorAllowed = value;
+ }
+
+ public synchronized void raiseNCS(NCS ncs) {
+ thisLoopNCS.put(ncs, thisLoopNCS.get(ncs) + 1);
+
+ if (ncs.equals(NCS.CONTEXT_CONFLICT_FALSE) || ncs.equals(NCS.HEAD_INCOMPETENT)) {
+ NCS.a = true;
+ }
+ }
+
+ public void changeNCSNumber(int x, NCS ncs) {
+ if (numberOfNCS.containsKey(ncs)) {
+ numberOfNCS.put(ncs, numberOfNCS.get(ncs) + x);
+ } else {
+ numberOfNCS.put(ncs, x);
+ }
+ }
+
+ public void trace(TRACE_LEVEL lvl, ArrayList<String> infos) {
+ if (lvl.isGE(minLevel)) {
+ String message = "[" +amoeba.getCycle() + "]";
+ for(String info : infos) {
+ message += " " + info;
+ }
+ System.out.println(message);
+ }
+
+ }
+
+ public double getAVT_acceleration() {
+ return AVT_acceleration;
+ }
+
+ public double getAVT_deceleration() {
+ return AVT_deceleration;
+ }
+
+ public double getAVT_percentAtStart() {
+ return AVT_percentAtStart;
+ }
+
+ public void preCycleActions() {
+ for (NCS ncs : NCS.values()) {
+ allTimeNCS.put(ncs, allTimeNCS.get(ncs) + thisLoopNCS.get(ncs));
+ thisLoopNCS.put(ncs, 0);
+ }
+ }
+
+ public HashMap<NCS, Integer> getThisLoopNCS() {
+ return thisLoopNCS;
+ }
+
+ public HashMap<NCS, Integer> getAllTimeNCS() {
+ return allTimeNCS;
+ }
+
+ public synchronized void incrementNbActivatedAgent() {
+ nbActivatedAgent += 1;
+ }
+
+ public int getNbActivatedAgent() {
+ return nbActivatedAgent;
+ }
+
+ public void resetNbActivatedAgent() {
+ nbActivatedAgent = 0;
+ }
+
+ public void setAmoeba(AMOEBA amoeba) {
+ this.amoeba = amoeba;
+ }
+
+ public double getIncrements() {
+ return increment_up ;
+ }
+
+ public double getContextCreationNeighborhood(Context ctxt, Percept pct) {
+ //return 2*ctxt.getRanges().get(pct).getRadius();
+ return pct.getRadiusContextForCreation()*2;
+ }
+
+ public double getContextNeighborhood(Context ctxt, Percept pct) {
+ //return 2*ctxt.getRanges().get(pct).getRadius();
+ return ctxt.getRanges().get(pct).getRadius();
+ }
+}
diff --git a/AMOEBAonAMAK/src/kernel/BackupSystem.java b/AMOEBAonAMAK/src/kernel/backup/BackupSystem.java
similarity index 67%
rename from AMOEBAonAMAK/src/kernel/BackupSystem.java
rename to AMOEBAonAMAK/src/kernel/backup/BackupSystem.java
index cfb954e2332255e35f8caa70b8764ecff6b68845..dcb6f72cbed6ef14922c82033642c7dc47370367 100644
--- a/AMOEBAonAMAK/src/kernel/BackupSystem.java
+++ b/AMOEBAonAMAK/src/kernel/backup/BackupSystem.java
@@ -1,9 +1,10 @@
-package kernel;
+package kernel.backup;
import java.io.File;
import java.io.FileWriter;
import java.io.IOException;
import java.util.ArrayList;
+import java.util.Comparator;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
@@ -24,12 +25,13 @@ import agents.context.Context;
import agents.context.Experiment;
import agents.context.Range;
import agents.context.localModel.LocalModel;
-import agents.context.localModel.LocalModelAverage;
-import agents.context.localModel.LocalModelFirstExp;
import agents.context.localModel.LocalModelMillerRegression;
import agents.context.localModel.TypeLocalModel;
import agents.head.Head;
import agents.percept.Percept;
+import kernel.AMOEBA;
+import kernel.AmoebaData;
+import utils.XMLSerialization;
/**
* @author Labbeti
@@ -42,8 +44,9 @@ public class BackupSystem implements IBackupSystem {
// Members
private AMOEBA amoeba;
- private Map<String, Percept> perceptsByName= new HashMap<>();
+ private Map<String, Percept> perceptsByName = new HashMap<>();
private boolean loadPresetContext = true;
+ private boolean amoebaDataLoaded = false;
// -------------------- Constructor --------------------
@@ -88,21 +91,21 @@ public class BackupSystem implements IBackupSystem {
XMLOutputter xml = new XMLOutputter();
xml.setFormat(Format.getPrettyFormat());
- try (FileWriter fw = new FileWriter(file)){
+ try (FileWriter fw = new FileWriter(file)) {
xml.output(doc, fw);
} catch (IOException e) {
e.printStackTrace();
}
}
-
+
public void setLoadPresetContext(boolean loadPresetContext) {
this.loadPresetContext = loadPresetContext;
}
-
+
public boolean isLoadPresetContext() {
return loadPresetContext;
}
-
+
@Override
public String getExtension() {
return "xml";
@@ -123,16 +126,37 @@ public class BackupSystem implements IBackupSystem {
} catch (DataConversionException e) {
e.printStackTrace();
}
+
+ // amoeba data
+ Element dataElement = configurationElement.getChild("Data");
+ if(dataElement != null) { // the data field is optionnal. We don't ask human to write it !
+ XMLSerialization<AmoebaData> decode = new XMLSerialization<>();
+ amoeba.data = decode.fromString(dataElement.getText());
+ amoebaDataLoaded = true;
+ }
}
private void loadStartingAgents(Element systemElement) {
Element startingAgentsElement = systemElement.getChild("StartingAgents");
- List<Element> agentsElement = startingAgentsElement.getChildren();
+ List<Element> agentsElement = new ArrayList<>(startingAgentsElement.getChildren());
int nbHeadsAdded = 0;
int nbPerceptsAdded = 0;
+
+ // load head first
+ agentsElement.sort(new Comparator<Element>() {
+ @Override
+ public int compare(Element o1, Element o2) {
+ if(o1.getName().equals(HEAD_NODE))
+ return -1;
+ else if(o1.getName().equals(PERCEPT_NODE))
+ return 1;
+ else
+ return 0;
+ }
+ });
+
for (Element startingAgentElement : agentsElement) {
-
switch (startingAgentElement.getName()) {
case HEAD_NODE:
loadController(startingAgentElement);
@@ -154,22 +178,23 @@ public class BackupSystem implements IBackupSystem {
if (nbPerceptsAdded == 0) {
throw new IllegalDataException("Cannot load an AMOEBA without at least 1 Percept agent.");
}
+
+ amoeba.addPendingAgents();
}
private void loadPresetContexts(Element systemElement) {
Element presetContextsElement = systemElement.getChild("PresetContexts");
-
+
Element lastPerceptionsAndActionState = presetContextsElement.getChild("LastPerceptionsAndActionState");
- if(lastPerceptionsAndActionState != null) {
+ if (lastPerceptionsAndActionState != null) {
HashMap<String, Double> perceptionAndAction = new HashMap<>();
- for(Attribute att : lastPerceptionsAndActionState.getAttributes()) {
+ for (Attribute att : lastPerceptionsAndActionState.getAttributes()) {
perceptionAndAction.put(att.getName(), Double.valueOf(att.getValue()));
}
amoeba.setPerceptionsAndActionState(perceptionAndAction);
}
-
+
List<Element> contextsElement = presetContextsElement.getChildren("Context");
-
for (Element contextElement : contextsElement) {
loadContext(contextElement);
@@ -180,39 +205,23 @@ public class BackupSystem implements IBackupSystem {
Head head = new Head(amoeba);
head.setName(controllerElement.getAttributeValue("Name"));
head.setNoCreation(!amoeba.isCreationOfNewContext());
-
- // TODO (Labbeti): maybe set default values if you cant find errorMargin and
- // inexactMargin ?
- // head.setDataForErrorMargin(1000, 5, 0.4, 0.1, 40, 80);
- // head.setDataForInexactMargin(500, 2.5, 0.2, 0.05, 40, 80);
-
- Element errorMarginElement = controllerElement.getChild("ErrorMargin");
- double errorAllowed = Double.valueOf(errorMarginElement.getAttributeValue("ErrorAllowed"));
- double augmentationFactorError = Double
- .valueOf(errorMarginElement.getAttributeValue("AugmentationFactorError"));
- double diminutionFactorError = Double.valueOf(errorMarginElement.getAttributeValue("DiminutionFactorError"));
- double minErrorAllowed = Double.valueOf(errorMarginElement.getAttributeValue("MinErrorAllowed"));
- int nConflictBeforeAugmentation = Integer
- .valueOf(errorMarginElement.getAttributeValue("NConflictBeforeAugmentation"));
- int nSuccessBeforeDiminution = Integer
- .valueOf(errorMarginElement.getAttributeValue("NConflictBeforeAugmentation"));
- head.setDataForErrorMargin(errorAllowed, augmentationFactorError, diminutionFactorError, minErrorAllowed,
- nConflictBeforeAugmentation, nSuccessBeforeDiminution);
-
- Element inexactMarginElement = controllerElement.getChild("InexactMargin");
- double inexactAllowed = Double.valueOf(inexactMarginElement.getAttributeValue("InexactAllowed"));
- double augmentationInexactError = Double
- .valueOf(inexactMarginElement.getAttributeValue("AugmentationInexactError"));
- double diminutionInexactError = Double
- .valueOf(inexactMarginElement.getAttributeValue("DiminutionInexactError"));
- double minInexactAllowed = Double.valueOf(inexactMarginElement.getAttributeValue("MinInexactAllowed"));
- int nConflictBeforeInexactAugmentation = Integer
- .valueOf(inexactMarginElement.getAttributeValue("NConflictBeforeInexactAugmentation"));
- int nSuccessBeforeInexactDiminution = Integer
- .valueOf(inexactMarginElement.getAttributeValue("NSuccessBeforeInexactDiminution"));
- head.setDataForInexactMargin(inexactAllowed, augmentationInexactError, diminutionInexactError,
- minInexactAllowed, nConflictBeforeInexactAugmentation, nSuccessBeforeInexactDiminution);
-
+
+ if(!amoebaDataLoaded) {
+ // If no AmoebaData was loaded, then we need to initialize the head a bit more :
+ Element errorMarginElement = controllerElement.getChild("ErrorMargin");
+ double errorAllowed = Double.valueOf(errorMarginElement.getAttributeValue("ErrorAllowed"));
+ double augmentationFactorError = Double
+ .valueOf(errorMarginElement.getAttributeValue("AugmentationFactorError"));
+ double diminutionFactorError = Double.valueOf(errorMarginElement.getAttributeValue("DiminutionFactorError"));
+ double minErrorAllowed = Double.valueOf(errorMarginElement.getAttributeValue("MinErrorAllowed"));
+ int nConflictBeforeAugmentation = Integer
+ .valueOf(errorMarginElement.getAttributeValue("NConflictBeforeAugmentation"));
+ int nSuccessBeforeDiminution = Integer
+ .valueOf(errorMarginElement.getAttributeValue("NConflictBeforeAugmentation"));
+ head.setDataForErrorMargin(errorAllowed, augmentationFactorError, diminutionFactorError, minErrorAllowed,
+ nConflictBeforeAugmentation, nSuccessBeforeDiminution);
+ }
+
amoeba.setHead(head);
}
@@ -221,48 +230,64 @@ public class BackupSystem implements IBackupSystem {
percept.setName(sensorElement.getAttributeValue("Name"));
boolean isEnum = Boolean.valueOf(sensorElement.getAttributeValue("Enum"));
percept.setEnum(isEnum);
+ String max = sensorElement.getAttributeValue("Max");
+ if(max != null) percept.setMax(Double.valueOf(max));
+ String min = sensorElement.getAttributeValue("Min");
+ if(min != null) percept.setMin(Double.valueOf(min));
perceptsByName.put(percept.getName(), percept);
}
private void loadContext(Element contextElement) {
+ Context context = new Context(amoeba);
+
// -- Load Ranges
Element rangesElement = contextElement.getChild("Ranges");
- Map<Percept, Double> starts = new HashMap<>();
- Map<Percept, Double> ends = new HashMap<>();
- loadRanges(rangesElement, starts, ends);
+ loadRanges(context, rangesElement);
+ // -- Load Local Model
+ loadLocalModel(context, contextElement);
+
+ // -- Load attributes
+ context.setName(contextElement.getAttributeValue("Name"));
+ context.setConfidence(Double.valueOf(contextElement.getAttributeValue("Confidence")));
+ for(Percept p : amoeba.getPercepts()) {
+ p.updateContextProjectionEnd(context);
+ p.updateContextProjectionStart(context);
+ }
+
+ }
+
+ private void loadLocalModel(Context context, Element parentElement) {
+ Element localModelElement = parentElement.getChild("LocalModel");
+
// -- Load Experiments
- Element experimentsElement = contextElement.getChild("Experiments");
+ Element experimentsElement = localModelElement.getChild("Experiments");
ArrayList<Experiment> experiments = new ArrayList<>();
- loadExperiments(experimentsElement, experiments);
-
- // -- Load attributes
- String contextName = contextElement.getAttributeValue("Name");
- String localModelName = contextElement.getChild("LocalModel").getAttributeValue("Type");
+ loadExperiments(experiments ,context, experimentsElement);
+
+ // -- Load Model
+ String localModelName = localModelElement.getAttributeValue("Type");
TypeLocalModel type = TypeLocalModel.valueOf(localModelName);
LocalModel localModel;
switch (type) {
- case AVERAGE:
- localModel = new LocalModelAverage();
- break;
- case FIRST_EXPERIMENT:
- localModel = new LocalModelFirstExp();
- break;
case MILLER_REGRESSION:
- localModel = new LocalModelMillerRegression(starts.size());
+ List<Double> coefs = new ArrayList<>();
+ for(Element e : localModelElement.getChild("Coefs").getChildren()) {
+ coefs.add(Double.valueOf(e.getAttributeValue("v")));
+ }
+ localModel = new LocalModelMillerRegression(context, coefs.toArray(new Double[coefs.size()]), experiments);
break;
default:
throw new IllegalArgumentException("Found unknown model " + localModelName + " in XML file. ");
}
- double confidence = Double.valueOf(contextElement.getAttributeValue("Confidence"));
-
- // -- Create context
- Head head = amoeba.getHeads().get(0);
- new Context(amoeba, head, contextName, starts, ends, experiments, localModel, confidence);
+ context.setLocalModel(localModel);
+
+
}
- private void loadRanges(Element elemRanges, Map<Percept, Double> starts, Map<Percept, Double> ends) {
+ private void loadRanges(Context context, Element elemRanges) {
+ HashMap<Percept, Range> ranges = new HashMap<>();
for (Element rangeElement : elemRanges.getChildren()) {
String perceptName = rangeElement.getAttributeValue(PERCEPT_NODE);
double start = Double.valueOf(rangeElement.getAttributeValue("Start"));
@@ -274,18 +299,19 @@ public class BackupSystem implements IBackupSystem {
}
Percept percept = perceptsByName.get(perceptName);
- starts.put(percept, start);
- ends.put(percept, end);
+ Range range = new Range(context, start, end, 0, true, true, percept);
+ ranges.put(percept, range);
}
+ context.setRanges(ranges);
}
- private void loadExperiments(Element experimentsElement, List<Experiment> experiments) {
+ private void loadExperiments(List<Experiment> experiments, Context context, Element experimentsElement) {
for (Element experimentElement : experimentsElement.getChildren()) {
Element valuesElement = experimentElement.getChild("Values");
- Experiment experiment = new Experiment();
+ Experiment experiment = new Experiment(context);
double proposition = Double.valueOf(experimentElement.getAttributeValue("Proposition"));
- experiment.setProposition(proposition);
+ experiment.setOracleProposition(proposition);
for (Element valueElement : valuesElement.getChildren()) {
String perceptName = valueElement.getAttributeValue(PERCEPT_NODE);
@@ -311,8 +337,14 @@ public class BackupSystem implements IBackupSystem {
learningAttributes.add(new Attribute("creationOfNewContext", String.valueOf(amoeba.isCreationOfNewContext())));
learningAttributes.add(new Attribute("loadPresetContext", String.valueOf(isLoadPresetContext())));
learningElement.setAttributes(learningAttributes);
-
configurationElement.addContent(learningElement);
+
+ // amoeba data
+ Element dataElement = new Element("Data");
+ XMLSerialization<AmoebaData> encode = new XMLSerialization<>();
+ dataElement.setText(encode.toString(amoeba.data));
+ configurationElement.addContent(dataElement);
+
rootElement.addContent(configurationElement);
}
@@ -332,19 +364,19 @@ public class BackupSystem implements IBackupSystem {
rootElement.addContent(startingAgentsElement);
}
- private void savePresetContexts(Element rootElement) {
+ private void savePresetContexts(Element rootElement) {
List<Context> contexts = amoeba.getContexts();
Element presetContextsElement = new Element("PresetContexts");
-
+
Element lastPerceptionsAndActionState = new Element("LastPerceptionsAndActionState");
HashMap<String, Double> perceptionAndAction = amoeba.getPerceptionsAndActionState();
List<Attribute> attributes = new ArrayList<>();
- for(String key : perceptionAndAction.keySet()) {
- attributes.add(new Attribute(key, ""+perceptionAndAction.get(key)));
+ for (String key : perceptionAndAction.keySet()) {
+ attributes.add(new Attribute(key, "" + perceptionAndAction.get(key)));
}
lastPerceptionsAndActionState.setAttributes(attributes);
presetContextsElement.addContent(lastPerceptionsAndActionState);
-
+
presetContextsElement.addContent(new Comment(" Nb contexts = " + String.valueOf(contexts.size()) + " "));
for (Context context : contexts) {
@@ -357,6 +389,7 @@ public class BackupSystem implements IBackupSystem {
}
private void saveController(Head head, Element startingAgentsElement) {
+
Element controllerElement = new Element(HEAD_NODE);
List<Attribute> attributes = new ArrayList<>();
@@ -365,33 +398,23 @@ public class BackupSystem implements IBackupSystem {
Element errorMarginElement = new Element("ErrorMargin");
List<Attribute> errorAttributes = new ArrayList<>();
- errorAttributes.add(new Attribute("ErrorAllowed", String.valueOf(head.getErrorAllowed())));
- errorAttributes.add(new Attribute("AugmentationFactorError", String.valueOf(head.getAugmentationFactorError())));
- errorAttributes.add(new Attribute("DiminutionFactorError", String.valueOf(head.getDiminutionFactorError())));
- errorAttributes.add(new Attribute("MinErrorAllowed", String.valueOf(head.getMinErrorAllowed())));
- errorAttributes.add(
- new Attribute("NConflictBeforeAugmentation", String.valueOf(head.getNConflictBeforeAugmentation())));
errorAttributes
- .add(new Attribute("NSuccessBeforeDiminution", String.valueOf(head.getNSuccessBeforeDiminution())));
+ .add(new Attribute("ErrorAllowed", String.valueOf(head.getAmas().data.predictionPerformance.performanceIndicator)));
+ errorAttributes.add(new Attribute("AugmentationFactorError",
+ String.valueOf(head.getAmas().data.predictionPerformance.augmentationFactor)));
+ errorAttributes.add(
+ new Attribute("DiminutionFactorError", String.valueOf(head.getAmas().data.predictionPerformance.diminutionFactor)));
+ errorAttributes.add(
+ new Attribute("MinErrorAllowed", String.valueOf(head.getAmas().data.predictionPerformance.minPerformanceIndicator)));
+ errorAttributes.add(new Attribute("NConflictBeforeAugmentation",
+ String.valueOf(head.getAmas().data.predictionPerformance.conflictsBeforeAugmentation)));
+ errorAttributes.add(new Attribute("NSuccessBeforeDiminution",
+ String.valueOf(head.getAmas().data.predictionPerformance.successesBeforeDiminution)));
errorMarginElement.setAttributes(errorAttributes);
controllerElement.addContent(errorMarginElement);
- Element inexactMarginElement = new Element("InexactMargin");
- List<Attribute> inexactAttributes = new ArrayList<>();
- inexactAttributes.add(new Attribute("InexactAllowed", String.valueOf(head.getInexactAllowed())));
- inexactAttributes
- .add(new Attribute("AugmentationInexactError", String.valueOf(head.getAugmentationInexactError())));
- inexactAttributes
- .add(new Attribute("DiminutionInexactError", String.valueOf(head.getDiminutionInexactError())));
- inexactAttributes.add(new Attribute("MinInexactAllowed", String.valueOf(head.getMinInexactAllowed())));
- inexactAttributes.add(new Attribute("NConflictBeforeInexactAugmentation",
- String.valueOf(head.getNConflictBeforeInexactAugmentation())));
- inexactAttributes.add(new Attribute("NSuccessBeforeInexactDiminution",
- String.valueOf(head.getNSuccessBeforeInexactDiminution())));
- inexactMarginElement.setAttributes(inexactAttributes);
- controllerElement.addContent(inexactMarginElement);
-
startingAgentsElement.addContent(controllerElement);
+
}
private void saveSensor(Percept percept, Element startingAgentsElement) {
@@ -400,6 +423,8 @@ public class BackupSystem implements IBackupSystem {
attributes.add(new Attribute("Name", percept.getName()));
attributes.add(new Attribute("Enum", String.valueOf(percept.isEnum())));
+ attributes.add(new Attribute("Max", percept.getMax()+""));
+ attributes.add(new Attribute("Min", percept.getMin()+""));
sensorElement.setAttributes(attributes);
startingAgentsElement.addContent(sensorElement);
}
@@ -411,10 +436,6 @@ public class BackupSystem implements IBackupSystem {
HashMap<Percept, Range> ranges = context.getRanges();
saveRanges(ranges, contextElement);
- // -- Saving Experiments
- ArrayList<Experiment> experiments = context.getExperiments();
- saveExperiments(experiments, contextElement);
-
// -- Saving Local Model
saveLocalModel(context, contextElement);
@@ -422,8 +443,9 @@ public class BackupSystem implements IBackupSystem {
List<Attribute> agentAttributes = new ArrayList<>();
agentAttributes.add(new Attribute("Name", String.valueOf(context.getName())));
agentAttributes.add(new Attribute("Confidence", String.valueOf(context.getConfidence())));
- agentAttributes.add(new Attribute("ActionsProposal", context.getActionProposal()+""));
- agentAttributes.add(new Attribute("Activated", amoeba.getValidContexts().contains(context)+""));
+ agentAttributes.add(new Attribute("ActionsProposal", context.getActionProposal() + ""));
+ if(context.getAmas().getValidContexts() != null)
+ agentAttributes.add(new Attribute("Activated", (context.getAmas().getValidContexts().contains(context)) + ""));
contextElement.setAttributes(agentAttributes);
presetContextsElement.addContent(contextElement);
@@ -432,16 +454,21 @@ public class BackupSystem implements IBackupSystem {
private void saveLocalModel(Context context, Element contextElement) {
Element localModelElement = new Element("LocalModel");
localModelElement.setAttribute("Type", context.getFunction().getType().name());
-
+
+ // save coef
Element coefs = new Element("Coefs");
List<Element> coefsElements = new ArrayList<>();
- for(double c : context.getFunction().getCoefs()) {
- coefsElements.add(new Element("Value").setAttribute("v", c+""));
+ for (double c : context.getFunction().getCoef()) {
+ coefsElements.add(new Element("Value").setAttribute("v", c + ""));
}
coefs.addContent(coefsElements);
-
localModelElement.addContent(coefs);
- contextElement.addContent(localModelElement);
+
+ // -- Saving Experiments
+ ArrayList<Experiment> experiments = context.getLocalModel().getFirstExperiments();
+ saveExperiments(experiments, localModelElement);
+
+ contextElement.addContent(localModelElement);
}
private void saveRanges(Map<Percept, Range> ranges, Element contextElement) {
@@ -461,10 +488,10 @@ public class BackupSystem implements IBackupSystem {
contextElement.addContent(rangesElement);
}
- private void saveExperiments(List<Experiment> experiments, Element contextElement) {
+ private void saveExperiments(List<Experiment> experiments, Element parentElement) {
Element experimentsElement = new Element("Experiments");
for (Experiment experiment : experiments) {
- Map<Percept, Double> values = experiment.getValues();
+ Map<Percept, Double> values = experiment.getValuesAsHashMap();
Element valuesElement = new Element("Values");
for (Entry<Percept, Double> entry : values.entrySet()) {
@@ -482,10 +509,11 @@ public class BackupSystem implements IBackupSystem {
Element experimentElement = new Element("Experiment");
experimentElement.addContent(valuesElement);
- experimentElement.setAttribute(new Attribute("Proposition", String.valueOf(experiment.getProposition())));
+ experimentElement
+ .setAttribute(new Attribute("Proposition", String.valueOf(experiment.getOracleProposition())));
experimentsElement.addContent(experimentElement);
}
- contextElement.addContent(experimentsElement);
+ parentElement.addContent(experimentsElement);
}
}
diff --git a/AMOEBAonAMAK/src/kernel/IBackupSystem.java b/AMOEBAonAMAK/src/kernel/backup/IBackupSystem.java
similarity index 97%
rename from AMOEBAonAMAK/src/kernel/IBackupSystem.java
rename to AMOEBAonAMAK/src/kernel/backup/IBackupSystem.java
index 0151a0b17d0db5d04f57d32c0a94d0a87c6a5d18..ec388ff989147192bb77c2a24956d7da6ee9c85b 100644
--- a/AMOEBAonAMAK/src/kernel/IBackupSystem.java
+++ b/AMOEBAonAMAK/src/kernel/backup/IBackupSystem.java
@@ -1,4 +1,4 @@
-package kernel;
+package kernel.backup;
import java.io.File;
diff --git a/AMOEBAonAMAK/src/kernel/backup/ISaveHelper.java b/AMOEBAonAMAK/src/kernel/backup/ISaveHelper.java
new file mode 100644
index 0000000000000000000000000000000000000000..6b9c17d3c9788553a01c04eef68b2a4bfa1709c4
--- /dev/null
+++ b/AMOEBAonAMAK/src/kernel/backup/ISaveHelper.java
@@ -0,0 +1,72 @@
+package kernel.backup;
+
+import java.io.File;
+import java.nio.file.Path;
+import java.util.List;
+
+/**
+ * An helper class that handle save, autosave, and load needs of an AMOEBA.
+ * @see SaveHelperImpl
+ * @see SaveHelperDummy
+ * @author Hugo
+ *
+ */
+public interface ISaveHelper {
+
+ /**
+ * Load a save pointed by path.
+ * @param path path to the save.
+ */
+ public void load(String path);
+
+ /**
+ * Load a save from file.
+ * @param path path to the save.
+ */
+ public void load(File file);
+
+ /**
+ * Create a save at path.
+ * @param path path of the new save
+ */
+ public void save(String path);
+
+ /**
+ * Create a save in file.
+ * @param path path of the new save
+ */
+ public void save(File file);
+
+ /**
+ * Add a new save in {@link SaveHelperImpl#dirManual}.
+ * @param name
+ */
+ public void newManualSave(String name);
+
+ /**
+ * Add a new save in {@link SaveHelperImpl#dirAuto}.
+ */
+ public void autosave();
+
+ /**
+ * List saves in {@link SaveHelperImpl#dirAuto}.
+ */
+ public List<Path> listAutoSaves();
+
+ /**
+ * List saves in {@link SaveHelperImpl#dirManual}.
+ */
+ public List<Path> listManualSaves();
+
+ /**
+ * Activate or deactivate the automatic save system.
+ * @param value
+ */
+ public void setAutoSave(boolean value);
+
+ /**
+ * Tell if the automatic save system is activated.
+ * @return
+ */
+ public boolean getAutoSave();
+}
diff --git a/AMOEBAonAMAK/src/kernel/backup/SaveHelperDummy.java b/AMOEBAonAMAK/src/kernel/backup/SaveHelperDummy.java
new file mode 100644
index 0000000000000000000000000000000000000000..9166f2653ca2cd30d342f6e35f53ab4e1d9c5f3e
--- /dev/null
+++ b/AMOEBAonAMAK/src/kernel/backup/SaveHelperDummy.java
@@ -0,0 +1,61 @@
+package kernel.backup;
+
+import java.io.File;
+import java.nio.file.Path;
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * A save helper that does nothing. Useful when one wish to deactivate an amoeba save system.
+ *
+ * @see SaveHelperImpl
+ * @author Hugo
+ *
+ */
+public class SaveHelperDummy implements ISaveHelper {
+
+ @Override
+ public void load(String path) {
+ }
+
+ @Override
+ public void load(File file) {
+ }
+
+ @Override
+ public void save(String path) {
+ }
+
+ @Override
+ public void save(File file) {
+ }
+
+ @Override
+ public void newManualSave(String name) {
+ }
+
+ @Override
+ public void autosave() {
+ }
+
+ @Override
+ public List<Path> listAutoSaves() {
+ return new ArrayList<Path>();
+ }
+
+ @Override
+ public List<Path> listManualSaves() {
+ return new ArrayList<Path>();
+ }
+
+ @Override
+ public void setAutoSave(boolean value) {
+
+ }
+
+ @Override
+ public boolean getAutoSave() {
+ return false;
+ }
+
+}
diff --git a/AMOEBAonAMAK/src/kernel/SaveHelper.java b/AMOEBAonAMAK/src/kernel/backup/SaveHelperImpl.java
similarity index 75%
rename from AMOEBAonAMAK/src/kernel/SaveHelper.java
rename to AMOEBAonAMAK/src/kernel/backup/SaveHelperImpl.java
index 643e10827172b8d1fd38a3cc5df6222cf47e2d66..b2258c51d799c99816a3b9d049b84901f5374c1f 100644
--- a/AMOEBAonAMAK/src/kernel/SaveHelper.java
+++ b/AMOEBAonAMAK/src/kernel/backup/SaveHelperImpl.java
@@ -1,28 +1,31 @@
-package kernel;
+package kernel.backup;
import java.io.File;
import java.io.IOException;
import java.nio.file.DirectoryStream;
import java.nio.file.Files;
-import java.nio.file.LinkOption;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.ArrayList;
import java.util.List;
+import fr.irit.smac.amak.Configuration;
import fr.irit.smac.amak.ui.MainWindow;
import gui.AmoebaWindow;
import gui.saveExplorer.SaveExplorer;
import javafx.event.ActionEvent;
import javafx.event.EventHandler;
import javafx.stage.FileChooser;
+import kernel.AMOEBA;
+import utils.DeleteDirectory;
/**
- * An helper class that handle save, autosave, and load needs of an AMOEBA.
+ * The standard implementation of {@link ISaveHelper}
+ * @see SaveHelperDummy
* @author Hugo
*
*/
-public class SaveHelper {
+public class SaveHelperImpl implements ISaveHelper{
/**
* Path to the saves' root directory. Default is 'saves'.
*/
@@ -36,12 +39,13 @@ public class SaveHelper {
public IBackupSystem backupSystem;
/**
- * If false {@link SaveHelper#autosave()} will do nothing.
+ * If false {@link SaveHelperImpl#autosave()} will do nothing.<br/>
+ * Default at not( {@link Configuration#commandLineMode} ).
*/
public boolean autoSave = true;
/**
- * Will the SaveHelper delete {@link SaveHelper#dir} when closing the MainWindow ?
+ * Will the SaveHelper delete {@link SaveHelperImpl#dir} when closing the MainWindow ?
*/
public boolean deleteFolderOnClose = true;
@@ -58,18 +62,19 @@ public class SaveHelper {
/**
* Path to the save directory.
*/
- private Path dir;
+ public Path dir;
private AMOEBA amoeba;
/**
* Create a SaveHelper for an amoeba.<br/>
- * Saves are stored in {@link SaveHelper#savesRoot}, under a directory named after the amoeba and creation time of the SaveHelper.<br/>
- * Autosave for this SaveHelper can be deactivated with {@link SaveHelper#autoSave}.<br/>
- * By default, the save folder for this amoeba is deleted when the application is closed, this can be changed with {@link SaveHelper#deleteFolderOnClose}.
+ * Saves are stored in {@link SaveHelperImpl#savesRoot}, under a directory named after the amoeba and creation time of the SaveHelper.<br/>
+ * Autosave for this SaveHelper can be deactivated with {@link SaveHelperImpl#autoSave}.<br/>
+ * By default, the save folder for this amoeba is deleted when the application is closed, this can be changed with {@link SaveHelperImpl#deleteFolderOnClose}.
* @param amoeba
*/
- public SaveHelper(AMOEBA amoeba) {
+ public SaveHelperImpl(AMOEBA amoeba) {
+ autoSave = !Configuration.commandLineMode;
this.amoeba = amoeba;
backupSystem = new BackupSystem(amoeba);
String dirName = amoeba.toString() + "_" + System.currentTimeMillis();
@@ -101,7 +106,7 @@ public class SaveHelper {
AmoebaWindow.addOnCloseAction(()-> {
if(deleteFolderOnClose) {
try {
- deleteDirectoryRecursion(dir);
+ DeleteDirectory.deleteDirectoryRecursion(dir);
} catch (IOException e) {
e.printStackTrace();
System.err.println("Failed to delete saves files on close.");
@@ -112,45 +117,30 @@ public class SaveHelper {
}
}
- /**
- * Delete a directory and everything in it, recursively.
- * @param path
- * @throws IOException
- */
- private void deleteDirectoryRecursion(Path path) throws IOException {
- if (Files.isDirectory(path, LinkOption.NOFOLLOW_LINKS)) {
- try (DirectoryStream<Path> entries = Files.newDirectoryStream(path)) {
- for (Path entry : entries) {
- deleteDirectoryRecursion(entry);
- }
- }
- }
- Files.delete(path);
- }
-
- /**
- * Load a save pointed by path.
- * @param path path to the save.
- */
+ @Override
public void load(String path) {
File f = new File(path);
- backupSystem.load(f);
+ load(f);
+ }
+
+ @Override
+ public void load(File file) {
+ backupSystem.load(file);
}
- /**
- * Create a save at path.
- * @param path path of the new save
- */
+ @Override
public void save(String path) {
File f = new File(path);
+ save(f);
+ }
+
+ @Override
+ public void save(File file) {
backupSystem.setLoadPresetContext(true);
- backupSystem.save(f);
+ backupSystem.save(file);
}
- /**
- * Add a new save in {@link SaveHelper#dirManual}.
- * @param name
- */
+ @Override
public void newManualSave(String name) {
String c = (name == null || "".equals(name)) ? "" : ("_" + name);
c.replace('/', '-');
@@ -160,9 +150,7 @@ public class SaveHelper {
backupSystem.save(p.toFile());
}
- /**
- * Add a new save in {@link SaveHelper#dirAuto}.
- */
+ @Override
public void autosave() {
if (autoSave) {
Path p = Paths.get(dirAuto.toString(), amoeba.getCycle() + "." + backupSystem.getExtension());
@@ -171,9 +159,7 @@ public class SaveHelper {
}
}
- /**
- * List saves in {@link SaveHelper#dirAuto}.
- */
+ @Override
public List<Path> listAutoSaves() {
List<Path> l = new ArrayList<>();
try (DirectoryStream<Path> d = Files.newDirectoryStream(dirAuto)){
@@ -185,9 +171,7 @@ public class SaveHelper {
return l;
}
- /**
- * List saves in {@link SaveHelper#dirManual}.
- */
+ @Override
public List<Path> listManualSaves() {
List<Path> l = new ArrayList<>();
try (DirectoryStream<Path> d = Files.newDirectoryStream(dirManual)){
@@ -233,4 +217,14 @@ public class SaveHelper {
};
MainWindow.addOptionsItem("Save", eventSave);
}
+
+ @Override
+ public void setAutoSave(boolean value) {
+ autoSave = value;
+ }
+
+ @Override
+ public boolean getAutoSave() {
+ return autoSave;
+ }
}
diff --git a/AMOEBAonAMAK/src/ncs/NCS.java b/AMOEBAonAMAK/src/ncs/NCS.java
index e245a1998b8320a16777c22d5ef4105e9aa7e9fb..c2e85b02499b4420c6c782508e60e8f0ac600fd9 100644
--- a/AMOEBAonAMAK/src/ncs/NCS.java
+++ b/AMOEBAonAMAK/src/ncs/NCS.java
@@ -4,26 +4,31 @@ import java.io.Serializable;
import kernel.World;
+
/**
- * Non Cooperative Situation as defined in the AMAS theory.
- */
+ * Non Cooperative Situation as defined in the AMAS theory.
+ */
public enum NCS implements Serializable {
- /* Context NCS */
+
+
+
+ /*Context NCS*/
CONTEXT_CONFLICT_FALSE,
CONTEXT_CONFLICT_INEXACT,
CONTEXT_USELESSNESS,
CONTEXT_CONCURRENCE,
- CONTEXT_OVERLAP_CONFLICT,
- CONTEXT_OVERLAP_REDUNDANCY,
+ CONTEXT_OVERLAP_CONFLICT,
+ CONTEXT_OVERLAP_REDUNDANCY,
+ CONTEXT_OVERMAPPING,
- /* Head NCS */
+ /*Head NCS*/
HEAD_INCOMPETENT,
- HEAD_IMPRODUCTIVE,
+ HEAD_IMPRODUCTIVE,
CREATE_NEW_CONTEXT;
-
+
public static boolean a = false;
-
+
/**
* Change the number of NCS in the world.
*
@@ -31,9 +36,10 @@ public enum NCS implements Serializable {
*/
public void raiseNCS(World world) {
world.changeNCSNumber(1, this);
+ //System.out.println(this);
if (this.equals(NCS.CONTEXT_CONFLICT_FALSE)) {
a = true;
}
}
-
+
}
diff --git a/AMOEBAonAMAK/src/py4j/Main.java b/AMOEBAonAMAK/src/py4j/Main.java
new file mode 100644
index 0000000000000000000000000000000000000000..92e655d605a06ab6074ac40d733d2f62478ca2c3
--- /dev/null
+++ b/AMOEBAonAMAK/src/py4j/Main.java
@@ -0,0 +1,26 @@
+package py4j;
+
+import fr.irit.smac.amak.Configuration;
+import fr.irit.smac.amak.tools.Log;
+
+public class Main {
+
+ /*
+ * Setting static field in py4j is difficult, this class add methods to help with that
+ */
+ public static class Control{
+ public static void setComandLine(boolean value) {
+ Configuration.commandLineMode = value;
+ }
+
+ public static void setLogLevel(String level) {
+ Log.defaultMinLevel = Log.Level.valueOf(level);
+ }
+ }
+
+ public static void main(String[] args) {
+ GatewayServer server = new GatewayServer();
+ server.start();
+ }
+
+}
diff --git a/AMOEBAonAMAK/src/ros/Main.java b/AMOEBAonAMAK/src/ros/Main.java
new file mode 100644
index 0000000000000000000000000000000000000000..e5d502c6c7e510dba9e4612e0145f5fc8a0561b6
--- /dev/null
+++ b/AMOEBAonAMAK/src/ros/Main.java
@@ -0,0 +1,57 @@
+package ros;
+
+import fr.irit.smac.amak.Configuration;
+import kernel.AMOEBA;
+
+public class Main {
+
+ public static void main(String[] args) {
+ if(args.length < 5){
+ System.out.println(
+ "Usage : RosbridgeWebsocketURI ConfigFilePath RosToAmoebaTopic AmoebaToRosTopic MsgType [--nogui]"
+ + "\nRosbridge websocket URI example:\n\tws://localhost:9090"
+ + "\nConfig file example : \n\tresources/MyAmoebaConfig.xml"
+ + "\nRos to Amoeba topic example : \n\t/amoeba_req"
+ + "\nAmoeba to Ros topic example : \n\t/amoeba_res"
+ + "\nROS Message Type example : \n\tyour_ros_package/MyAmoebaMessageType"
+ );
+ System.exit(0);
+ }
+ String uri = args[0];
+ String config = args[1];
+ String topicSub = args[2];
+ String topicPub = args[3];
+ String msgType = args[4];
+ if(args.length > 5) {
+ for(int i = 5; i < args.length; i++) {
+ if("--nogui".equals(args[i])) {
+ Configuration.commandLineMode = true;
+ }
+ }
+ }
+
+ AMOEBA amoeba = new AMOEBA(config, null);
+ amoeba.allowGraphicalScheduler(false);
+
+ RosBridge bridge = new RosBridge();
+ bridge.connect(uri, true);
+ bridge.waitForConnection();
+
+ //How it work look a lot like a service
+
+ Publisher pub = new Publisher(topicPub, msgType, bridge);
+
+ bridge.subscribe(SubscriptionRequestMsg.generate(topicSub)
+ .setType(msgType)
+ .setThrottleRate(1)
+ .setQueueLength(1),
+ new RosListenDelegateForAmoeba(amoeba, pub)
+ );
+
+ try {
+ Thread.currentThread().join();
+ } catch (InterruptedException e) {
+ e.printStackTrace();
+ }
+ }
+}
diff --git a/AMOEBAonAMAK/src/ros/RosListenDelegateForAmoeba.java b/AMOEBAonAMAK/src/ros/RosListenDelegateForAmoeba.java
new file mode 100644
index 0000000000000000000000000000000000000000..5c4a49a1e99303c767c21bc6af973056e7e2614b
--- /dev/null
+++ b/AMOEBAonAMAK/src/ros/RosListenDelegateForAmoeba.java
@@ -0,0 +1,49 @@
+package ros;
+
+import java.util.HashMap;
+
+import com.fasterxml.jackson.databind.JsonNode;
+import com.fasterxml.jackson.databind.node.JsonNodeFactory;
+import com.fasterxml.jackson.databind.node.ObjectNode;
+
+import agents.percept.Percept;
+import kernel.AMOEBA;
+
+public class RosListenDelegateForAmoeba implements RosListenDelegate {
+
+ private AMOEBA amoeba;
+ private Publisher pub;
+
+ public RosListenDelegateForAmoeba(AMOEBA amoeba, Publisher pub) {
+ this.amoeba = amoeba;
+ this.pub = pub;
+ }
+
+ @Override
+ public void receive(JsonNode data, String stringRep) {
+ HashMap<String, Double> out = buildOutputFromMsg(data);
+ double res;
+ boolean learn = data.get("msg").get("learn").asBoolean();
+ if(learn) {
+ amoeba.learn(out);
+ res = amoeba.getAction();
+ } else {
+ res = amoeba.request(out);
+ }
+ ((ObjectNode)data.get("msg")).set("oracle", JsonNodeFactory.instance.numberNode(res));
+ pub.publishJsonMsg(data.get("msg").toString());
+ }
+
+ private HashMap<String, Double> buildOutputFromMsg(JsonNode data) {
+ HashMap<String, Double> output = new HashMap<>();
+ for(Percept p : amoeba.getPercepts()) {
+ String name = p.getName();
+ Double value = data.get("msg").get(name).asDouble();
+ output.put(name, value);
+ }
+ output.put("oracle", data.get("msg").get("oracle").asDouble());
+ return output;
+ }
+
+
+}
diff --git a/AMOEBAonAMAK/src/utils/DeleteDirectory.java b/AMOEBAonAMAK/src/utils/DeleteDirectory.java
new file mode 100644
index 0000000000000000000000000000000000000000..b9a6d382afaa0f7471786dbc6aa0a0ab41c26e24
--- /dev/null
+++ b/AMOEBAonAMAK/src/utils/DeleteDirectory.java
@@ -0,0 +1,25 @@
+package utils;
+
+import java.io.IOException;
+import java.nio.file.DirectoryStream;
+import java.nio.file.Files;
+import java.nio.file.LinkOption;
+import java.nio.file.Path;
+
+public class DeleteDirectory {
+ /**
+ * Delete a directory and everything in it, recursively.
+ * @param path
+ * @throws IOException
+ */
+ public static void deleteDirectoryRecursion(Path path) throws IOException {
+ if (Files.isDirectory(path, LinkOption.NOFOLLOW_LINKS)) {
+ try (DirectoryStream<Path> entries = Files.newDirectoryStream(path)) {
+ for (Path entry : entries) {
+ deleteDirectoryRecursion(entry);
+ }
+ }
+ }
+ Files.delete(path);
+ }
+}
diff --git a/AMOEBAonAMAK/src/utils/Pair.java b/AMOEBAonAMAK/src/utils/Pair.java
new file mode 100644
index 0000000000000000000000000000000000000000..aa54fb9a0bedfcdf285dc83b9289d079db8e9828
--- /dev/null
+++ b/AMOEBAonAMAK/src/utils/Pair.java
@@ -0,0 +1,28 @@
+package utils;
+
+public class Pair<A,B> {
+
+ public A a;
+ public B b;
+
+ public Pair(A a, B b) {
+ this.a = a;
+ this.b = b;
+ }
+
+ public A getA() {
+ return a;
+ }
+
+ public B getB() {
+ return b;
+ }
+
+ public void setA(A a) {
+ this.a = a;
+ }
+
+ public void setB(B b) {
+ this.b = b;
+ }
+}
diff --git a/AMOEBAonAMAK/src/utils/PrintOnce.java b/AMOEBAonAMAK/src/utils/PrintOnce.java
new file mode 100644
index 0000000000000000000000000000000000000000..2f844fbf139d630d4d20f416b6b5e0cd5609153b
--- /dev/null
+++ b/AMOEBAonAMAK/src/utils/PrintOnce.java
@@ -0,0 +1,15 @@
+package utils;
+
+import java.util.HashSet;
+
+public class PrintOnce {
+
+ static private HashSet<String> done = new HashSet<String>();
+
+ public static void print(String str) {
+ if(!done.contains(str)) {
+ System.err.println(str);
+ done.add(str);
+ }
+ }
+}
diff --git a/AMOEBAonAMAK/src/utils/Quadruplet.java b/AMOEBAonAMAK/src/utils/Quadruplet.java
new file mode 100644
index 0000000000000000000000000000000000000000..7972b28ec711e28353a0c98819f7878be0535539
--- /dev/null
+++ b/AMOEBAonAMAK/src/utils/Quadruplet.java
@@ -0,0 +1,50 @@
+package utils;
+
+public class Quadruplet<A,B,C,D> {
+
+ public A a;
+ public B b;
+ public C c;
+ public D d;
+
+ public Quadruplet(A a, B b, C c, D d) {
+ this.a = a;
+ this.b = b;
+ this.c = c;
+ this.d = d;
+ }
+
+ public A getA() {
+ return a;
+ }
+
+ public B getB() {
+ return b;
+ }
+
+ public C getC() {
+ return c;
+ }
+
+ public D getD() {
+ return d;
+ }
+
+ public void setA(A a) {
+ this.a = a;
+ }
+
+ public void setB(B b) {
+ this.b = b;
+ }
+
+ public void setC(C c) {
+ this.c = c;
+ }
+
+ public void setD(D d) {
+ this.d = d;
+ }
+}
+
+
diff --git a/AMOEBAonAMAK/src/utils/RandomUtils.java b/AMOEBAonAMAK/src/utils/RandomUtils.java
new file mode 100644
index 0000000000000000000000000000000000000000..9440f17725430ccad2abcee4edb6470d61072134
--- /dev/null
+++ b/AMOEBAonAMAK/src/utils/RandomUtils.java
@@ -0,0 +1,58 @@
+package utils;
+
+import java.util.Collections;
+import java.util.List;
+import java.util.Random;
+import java.util.concurrent.ThreadLocalRandom;
+
+public class RandomUtils {
+
+ /**
+ * Pick N random element from the list. if n is bigger than the list, return the list.
+ * Use Durstenfeld's algorithm
+ * @param <E>
+ * @param list
+ * @param n
+ * @param r
+ * @return
+ */
+ public static <E> List<E> pickNRandomElements(List<E> list, int n, Random r) {
+ int length = list.size();
+
+ if (length < n) return list;
+
+ //We don't need to shuffle the whole list
+ for (int i = length - 1; i >= length - n; --i)
+ {
+ Collections.swap(list, i , r.nextInt(i + 1));
+ }
+ return list.subList(length - n, length);
+ }
+
+ /**
+ * Pick N random element from the list. if n is bigger than the list, return the list.
+ * Use Durstenfeld's algorithm
+ * @param <E>
+ * @param list
+ * @param n
+ * @return
+ */
+ public static <E> List<E> pickNRandomElements(List<E> list, int n) {
+ return pickNRandomElements(list, n, ThreadLocalRandom.current());
+ }
+
+ /**
+ * Generate a pseudorandom double values, conforming to the given origin (inclusive) and bound(exclusive).
+ * @param rand
+ * @param origin the origin (inclusive) of the random value
+ * @param bound the bound (exclusive) of the random value
+ * @return
+ */
+ public static double nextDouble(Random rand, double origin, double bound) {
+ double r = rand.nextDouble();
+ r = r * (bound - origin) + origin;
+ if (r >= bound) // correct for rounding
+ r = Math.nextDown(bound);
+ return r;
+ }
+}
diff --git a/AMOEBAonAMAK/src/utils/Round.java b/AMOEBAonAMAK/src/utils/Round.java
new file mode 100644
index 0000000000000000000000000000000000000000..9cfe127c9246683749a3c015f17b09c730300f16
--- /dev/null
+++ b/AMOEBAonAMAK/src/utils/Round.java
@@ -0,0 +1,20 @@
+package utils;
+
+import java.math.BigDecimal;
+import java.math.RoundingMode;
+
+public class Round {
+ /**
+ * Round a value to its nth decimal
+ * @param value
+ * @param places
+ * @return
+ */
+ public static double round(double value, int places) {
+ if (places < 0) throw new IllegalArgumentException();
+
+ BigDecimal bd = new BigDecimal(value);
+ bd = bd.setScale(places, RoundingMode.HALF_UP);
+ return bd.doubleValue();
+ }
+}
diff --git a/AMOEBAonAMAK/src/utils/TRACE_LEVEL.java b/AMOEBAonAMAK/src/utils/TRACE_LEVEL.java
new file mode 100644
index 0000000000000000000000000000000000000000..bc2da4ad5f98cbdfc9969723dcc707528bba233d
--- /dev/null
+++ b/AMOEBAonAMAK/src/utils/TRACE_LEVEL.java
@@ -0,0 +1,15 @@
+package utils;
+
+public enum TRACE_LEVEL {
+ ERROR(200), NCS(100), EVENT(50), STATE(40), INFORM(20), DEBUG(0);
+
+ private final int order;
+
+ TRACE_LEVEL(final int order) {
+ this.order = order;
+ }
+
+ public boolean isGE(final TRACE_LEVEL _other) {
+ return order >= _other.order;
+ }
+}
diff --git a/AMOEBAonAMAK/src/utils/Triplet.java b/AMOEBAonAMAK/src/utils/Triplet.java
new file mode 100644
index 0000000000000000000000000000000000000000..c8a49119a7939a8d76e1c93af8317c30ad7933fa
--- /dev/null
+++ b/AMOEBAonAMAK/src/utils/Triplet.java
@@ -0,0 +1,40 @@
+package utils;
+
+public class Triplet<A,B,C> {
+
+ public A a;
+ public B b;
+ public C c;
+
+ public Triplet(A a, B b, C c) {
+ this.a = a;
+ this.b = b;
+ this.c = c;
+ }
+
+ public A getA() {
+ return a;
+ }
+
+ public B getB() {
+ return b;
+ }
+
+ public C getC() {
+ return c;
+ }
+
+ public void setA(A a) {
+ this.a = a;
+ }
+
+ public void setB(B b) {
+ this.b = b;
+ }
+
+ public void setC(C c) {
+ this.c = c;
+ }
+}
+
+
diff --git a/AMOEBAonAMAK/src/utils/XMLSerialization.java b/AMOEBAonAMAK/src/utils/XMLSerialization.java
new file mode 100644
index 0000000000000000000000000000000000000000..a1e59954ac31a732c145ee3026667ea115c4b90f
--- /dev/null
+++ b/AMOEBAonAMAK/src/utils/XMLSerialization.java
@@ -0,0 +1,41 @@
+package utils;
+
+import java.beans.XMLDecoder;
+import java.beans.XMLEncoder;
+import java.io.ByteArrayInputStream;
+import java.io.ByteArrayOutputStream;
+
+/**
+ * Encode/decode serializable object to/from XML
+ * @author Hugo
+ *
+ * @param <T>
+ */
+public class XMLSerialization<T> {
+
+ /**
+ * Encode a serializable object to a XML string
+ * @param obj
+ * @return
+ */
+ public String toString(T obj) {
+ ByteArrayOutputStream baos = new ByteArrayOutputStream();
+ XMLEncoder e = new XMLEncoder(baos);
+ e.writeObject(obj);
+ e.close();
+ return new String(baos.toByteArray());
+ }
+
+ /**
+ * Decode a serializable object from a XML string
+ * @param str
+ * @return
+ */
+ @SuppressWarnings("unchecked")
+ public T fromString(String str) {
+ XMLDecoder d = new XMLDecoder(new ByteArrayInputStream(str.getBytes()));
+ T obj = (T) d.readObject();
+ d.close();
+ return obj;
+ }
+}
diff --git a/AMOEBAonAMAK/src/utils/XmlConfigGenerator.java b/AMOEBAonAMAK/src/utils/XmlConfigGenerator.java
new file mode 100644
index 0000000000000000000000000000000000000000..3819e2af7c35df94763eab320fbacd78491f335e
--- /dev/null
+++ b/AMOEBAonAMAK/src/utils/XmlConfigGenerator.java
@@ -0,0 +1,61 @@
+package utils;
+
+import java.io.File;
+import java.io.FileWriter;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Locale;
+
+public class XmlConfigGenerator {
+
+ public static String header = "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n";
+ public static String systemStart = "<System>\n";
+ public static String configurationStart = "<Configuration>\n";
+ public static String configuration = " <Learning allowed = \"%s\" creationOfNewContext = \"%s\" loadPresetContext = \"%s\" />\n";
+ public static String configurationEnd = "</Configuration>\n";
+ public static String agentsStart = "<StartingAgents>\n";
+ public static String sensor = " <Sensor Name=\"%s\" Enum=\"%s\" />\n";
+ public static String controller = " <Controller Name=\"Controller\">\n" +
+ " <ErrorMargin ErrorAllowed=\"%f\" AugmentationFactorError=\"%f\" DiminutionFactorError=\"%f\" MinErrorAllowed=\"%f\" NConflictBeforeAugmentation=\"%d\" NSuccessBeforeDiminution=\"%d\" />\n" +
+ " </Controller>\n";
+ public static String agentsEnd = "</StartingAgents>\n";
+ public static String systemEnd = "</System>\n";
+
+ private static String makeSensor(String sensorName, boolean isEnum) {
+ return String.format(sensor, sensorName, ""+isEnum);
+ }
+
+ private static String makeConfiguration(boolean isLearningAllowed, boolean isCreationOfNewContext, boolean isLoadContext) {
+ return String.format(configuration, ""+isLearningAllowed, ""+isCreationOfNewContext, ""+isLoadContext);
+ }
+
+ private static String makeController(double errorAllowed, double augmentationFactorError, double diminutionFactorError, double minErrorAllowed, int nConflictBeforeAugmentation, int nSuccessBeforeDiminution) {
+ return String.format(Locale.ENGLISH, controller, errorAllowed, augmentationFactorError, diminutionFactorError, minErrorAllowed, nConflictBeforeAugmentation, nSuccessBeforeDiminution);
+ }
+
+ public static void makeXML(File file, List<Pair<String, Boolean>> sensors) throws IOException {
+ try(FileWriter fw = new FileWriter(file)){
+ fw.write(header);
+ fw.write(systemStart);
+ fw.write(configurationStart);
+ fw.write(makeConfiguration(true, true, false));
+ fw.write(configurationEnd);
+ fw.write(agentsStart);
+ for(Pair<String, Boolean> s : sensors) {
+ fw.write(makeSensor(s.getA(), s.getB()));
+ }
+ fw.write(makeController(1.0, 0.5, 0.5, 0.01, 50, 50));
+ fw.write(agentsEnd);
+ fw.write(systemEnd);
+ }
+ }
+
+ public static void makeXML(File file, int dimension) throws IOException {
+ ArrayList<Pair<String, Boolean>> sensors = new ArrayList<>(dimension);
+ for(int i = 1; i <= dimension; i++) {
+ sensors.add(new Pair<String, Boolean>("p"+i, false));
+ }
+ makeXML(file, sensors);
+ }
+}
diff --git a/AMOEBAonAMAK/tests/agents/TestContext.java b/AMOEBAonAMAK/tests/agents/TestContext.java
new file mode 100644
index 0000000000000000000000000000000000000000..ec8867345610182b2f127e839ecd7b80c8f8044f
--- /dev/null
+++ b/AMOEBAonAMAK/tests/agents/TestContext.java
@@ -0,0 +1,25 @@
+package agents;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+import org.junit.jupiter.api.Test;
+
+import agents.context.Context;
+import agents.percept.Percept;
+import utils.TestSetup;
+
+public class TestContext extends TestSetup {
+
+ /**
+ * Check that the context projection has the same range as the context
+ */
+ @Test
+ public void testCoherenceProjection() {
+ for(Context c : amoeba.getContexts()) {
+ for(Percept p : amoeba.getPercepts()) {
+ assertEquals(c.getRanges().get(p).getStart(), p.contextProjections.get(c).getStart());
+ assertEquals(c.getRanges().get(p).getEnd(), p.contextProjections.get(c).getEnd());
+ }
+ }
+ }
+}
diff --git a/AMOEBAonAMAK/tests/kernel/TestMaximize.java b/AMOEBAonAMAK/tests/kernel/TestMaximize.java
new file mode 100644
index 0000000000000000000000000000000000000000..b8674b9d27f03e2f82ccc377fc355c3b1b5fd2c1
--- /dev/null
+++ b/AMOEBAonAMAK/tests/kernel/TestMaximize.java
@@ -0,0 +1,67 @@
+package kernel;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+import java.io.File;
+import java.util.HashMap;
+import java.util.Random;
+
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Test;
+
+import fr.irit.smac.amak.Configuration;
+import kernel.backup.BackupSystem;
+import kernel.backup.SaveHelperDummy;
+import utils.Round;
+
+/**
+ * Tests for {@link AMOEBA#maximize(HashMap)}
+ * @author daavve
+ *
+ */
+public class TestMaximize {
+
+ AMOEBA amoeba;
+
+ @BeforeEach
+ public void setup() {
+ Configuration.allowedSimultaneousAgentsExecution = 1;
+ Configuration.commandLineMode = true;
+ amoeba = new AMOEBA("tests/kernel/simple_with_context.xml", null);
+ amoeba.saver = new SaveHelperDummy();
+ }
+
+ @Test
+ public void testNoResult() {
+ HashMap<String, Double> req = new HashMap<String, Double>();
+ req.put("px0", -30.0);
+ HashMap<String, Double> sol = amoeba.maximize(req);
+ assertEquals(Double.NEGATIVE_INFINITY, sol.get("oracle"));
+ }
+
+ @Test
+ public void testResult() {
+ HashMap<String, Double> req = new HashMap<String, Double>();
+ req.put("px0", 10.0);
+ HashMap<String, Double> sol = amoeba.maximize(req);
+ assertEquals(Round.round(2.429498684425507, 8), Round.round(sol.get("oracle"), 8));
+ }
+
+ @Test
+ public void testCoherenceRandom() {
+ // test coherence of result from request/maximize
+ Random rand = new Random();
+ for(int i = 0; i < 100; i++) {
+ HashMap<String, Double> req = new HashMap<String, Double>();
+ double px0 = rand.nextDouble();
+ req.put("px0", px0);
+ HashMap<String, Double> solMax = amoeba.maximize(req);
+ req.put("px1", solMax.get("px1"));
+ req.put("px2", solMax.get("px2"));
+ req.put("oracle", 0.0);
+ double res = amoeba.request(req);
+ assertEquals(Round.round(solMax.get("oracle"), 8), Round.round(res, 8));
+ }
+ }
+
+}
diff --git a/AMOEBAonAMAK/tests/kernel/simple_with_context.xml b/AMOEBAonAMAK/tests/kernel/simple_with_context.xml
new file mode 100644
index 0000000000000000000000000000000000000000..862739d6670eeb31d1a58f3dade64866895a0263
--- /dev/null
+++ b/AMOEBAonAMAK/tests/kernel/simple_with_context.xml
@@ -0,0 +1,912 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<System>
+ <Configuration>
+ <Learning creationOfNewContext="true" loadPresetContext="true" />
+ <Data><?xml version="1.0" encoding="UTF-8"?>
+<java version="1.8.0_171" class="java.beans.XMLDecoder">
+ <object class="kernel.AmoebaData" id="AmoebaData0">
+ <void class="kernel.AmoebaData" method="getField">
+ <string>nPropositionsReceived</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <int>1</int>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>prediction</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.013823391349333747</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>oracleValue</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.016507301905780793</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>oldOracleValue</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.03125912052032549</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>criticity</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.002683910556447046</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>distanceToRegression</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.002683874122615849</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>spatialGeneralizationScore</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>1993.8455704551088</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>noCreation</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <boolean>false</boolean>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>firstContext</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <boolean>true</boolean>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>contextFromPropositionWasSelected</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <boolean>true</boolean>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>selfRequest</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <object class="java.util.HashMap">
+ <void method="put">
+ <string>px1</string>
+ <double>-37.40972633944136</double>
+ </void>
+ <void method="put">
+ <string>px0</string>
+ <double>-89.03028902104312</double>
+ </void>
+ <void method="put">
+ <string>px2</string>
+ <double>66.62397977488465</double>
+ </void>
+ </object>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>maxConfidence</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>-Infinity</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>minConfidence</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>Infinity</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>maxPrediction</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>32.34723287261936</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>normalizedCriticality</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>8.297187481278713E-5</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>evolutionCriticalityPrediction</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.28767737498846424</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>evolutionCriticalityMapping</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.28767737498846424</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>evolutionCriticalityConfidence</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.28767737498846424</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>learningSpeed</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.01</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>numberOfPointsForRegression</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <int>100</int>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>contextNotFinished</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <boolean>true</boolean>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>predictionPerformance</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <object class="agents.head.DynamicPerformance" id="DynamicPerformance0">
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>successesBeforeDiminution</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <int>40</int>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>conflictsBeforeAugmentation</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <int>40</int>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>performanceIndicator</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <double>720.0</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>performanceCounter</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <int>19</int>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>augmentationFactor</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <double>5.0</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>diminutionFactor</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <double>0.4</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>minPerformanceIndicator</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <double>0.1</double>
+ </void>
+ </void>
+ </object>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>regressionPerformance</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <object class="agents.head.DynamicPerformance" id="DynamicPerformance1">
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>successesBeforeDiminution</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <int>100</int>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>conflictsBeforeAugmentation</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <int>100</int>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>performanceIndicator</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <double>200.0</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>augmentationFactor</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <double>0.5</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>diminutionFactor</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <double>0.5</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>minPerformanceIndicator</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <double>1.0</double>
+ </void>
+ </void>
+ </object>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>mappingPerformance</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <object class="agents.head.DynamicPerformance" id="DynamicPerformance2">
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>successesBeforeDiminution</string>
+ <void method="set">
+ <object idref="DynamicPerformance2"/>
+ <int>100000</int>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>conflictsBeforeAugmentation</string>
+ <void method="set">
+ <object idref="DynamicPerformance2"/>
+ <int>1000000</int>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>performanceIndicator</string>
+ <void method="set">
+ <object idref="DynamicPerformance2"/>
+ <double>0.05</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>augmentationFactor</string>
+ <void method="set">
+ <object idref="DynamicPerformance2"/>
+ <double>1.1</double>
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+ <string>diminutionFactor</string>
+ <void method="set">
+ <object idref="DynamicPerformance2"/>
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+ <string>minPerformanceIndicator</string>
+ <void method="set">
+ <object idref="DynamicPerformance2"/>
+ <double>1.0</double>
+ </void>
+ </void>
+ </object>
+ </void>
+ </void>
+ </object>
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+ <Context Name="1710089778" Confidence="4.0" ActionsProposal="0.6492511380905877">
+ <Ranges>
+ <Range Sensor="px2" Start="34.53998478742335" End="52.463591501702126" />
+ <Range Sensor="px1" Start="52.39051465636333" End="69.3929166335325" />
+ <Range Sensor="px0" Start="83.47071095819973" End="92.73511799252611" />
+ </Ranges>
+ <LocalModel Type="MILLER_REGRESSION">
+ <Coefs>
+ <Value v="0.6492511380905877" />
+ <Value v="-0.003758502626338107" />
+ <Value v="-0.002976906881950547" />
+ <Value v="-0.0024806365340499918" />
+ </Coefs>
+ <Experiments>
+ <Experiment Proposition="0.01165230000591596">
+ <Values>
+ <Value Sensor="px0" Value="92.73511799252611" />
+ <Value Sensor="px1" Value="60.89171564494791" />
+ <Value Sensor="px2" Value="43.50178814456274" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="0.014374983280504995">
+ <Values>
+ <Value Sensor="px0" Value="86.82359488797063" />
+ <Value Sensor="px1" Value="66.56747265497388" />
+ <Value Sensor="px2" Value="44.36171066392635" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="0.05161333115602449">
+ <Values>
+ <Value Sensor="px0" Value="85.03319402820276" />
+ <Value Sensor="px1" Value="55.363732255856924" />
+ <Value Sensor="px2" Value="45.20924980519741" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="0.05593892067291083">
+ <Values>
+ <Value Sensor="px0" Value="84.06142267719974" />
+ <Value Sensor="px1" Value="57.32664545540537" />
+ <Value Sensor="px2" Value="43.43265642635008" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="0.015117531607223882">
+ <Values>
+ <Value Sensor="px0" Value="87.42307527273056" />
+ <Value Sensor="px1" Value="59.45897642582164" />
+ <Value Sensor="px2" Value="51.92692316891513" />
+ </Values>
+ </Experiment>
+ </Experiments>
+ </LocalModel>
+ </Context>
+ <Context Name="121573526" Confidence="4.0" ActionsProposal="0.5948709844574692">
+ <Ranges>
+ <Range Sensor="px2" Start="56.652361133902815" End="74.57596784818159" />
+ <Range Sensor="px1" Start="-41.43976576473927" End="-24.437363787570114" />
+ <Range Sensor="px0" Start="-92.5530226940015" End="-81.89441318686536" />
+ </Ranges>
+ <LocalModel Type="MILLER_REGRESSION">
+ <Coefs>
+ <Value v="0.5948709844574692" />
+ <Value v="0.0037578164320726305" />
+ <Value v="0.0019687743924070985" />
+ <Value v="-0.0025747865390199636" />
+ </Coefs>
+ <Experiments>
+ <Experiment Proposition="0.017381945447668915">
+ <Values>
+ <Value Sensor="px0" Value="-91.15882022119175" />
+ <Value Sensor="px1" Value="-32.93856477615469" />
+ <Value Sensor="px2" Value="65.6141644910422" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="0.029993685915308783">
+ <Values>
+ <Value Sensor="px0" Value="-87.55530523803283" />
+ <Value Sensor="px1" Value="-37.95861863661977" />
+ <Value Sensor="px2" Value="62.540917652398655" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="0.05129384694921611">
+ <Values>
+ <Value Sensor="px0" Value="-88.28034336028085" />
+ <Value Sensor="px1" Value="-26.824061056870026" />
+ <Value Sensor="px2" Value="61.923141223397" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="0.03125912052032549">
+ <Values>
+ <Value Sensor="px0" Value="-84.44006029100552" />
+ <Value Sensor="px1" Value="-38.58651279593371" />
+ <Value Sensor="px2" Value="65.9352444292295" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="0.016507301905780793">
+ <Values>
+ <Value Sensor="px0" Value="-89.03028902104312" />
+ <Value Sensor="px1" Value="-37.40972633944136" />
+ <Value Sensor="px2" Value="66.62397977488465" />
+ </Values>
+ </Experiment>
+ </Experiments>
+ </LocalModel>
+ </Context>
+ </PresetContexts>
+</System>
diff --git a/AMOEBAonAMAK/tests/savesystem/TestBackupSystem.java b/AMOEBAonAMAK/tests/savesystem/TestBackupSystem.java
new file mode 100644
index 0000000000000000000000000000000000000000..17e2035b9847a84e0268a5405be457ee3147ffd3
--- /dev/null
+++ b/AMOEBAonAMAK/tests/savesystem/TestBackupSystem.java
@@ -0,0 +1,109 @@
+package savesystem;
+
+import static org.junit.jupiter.api.Assertions.assertArrayEquals;
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+import java.io.File;
+import java.io.IOException;
+
+import org.junit.jupiter.api.Test;
+
+import experiments.F_XY_System;
+import kernel.AMOEBA;
+import kernel.StudiedSystem;
+import utils.Round;
+import utils.TestSetup;
+
+/**
+ * AMOEBA is a chaotic system, small change at start can lead to vastly different result.
+ * Some of these test may fail for insignificant reason, in that case you can rerun the test, or ignore it.<br/>
+ * A possible reason for test failure happen when multiple context are valid, but it's usually rare,
+ * and unlikely to happen on small test sample.
+ *
+ * @author Hugo
+ *
+ */
+public class TestBackupSystem extends TestSetup{
+
+ @Test
+ public void testSize() throws IOException {
+ File tempFile = File.createTempFile("testSave", "xml");
+ tempFile.deleteOnExit();
+
+ amoeba.saver.save(tempFile);
+
+ StudiedSystem studiedSystem = new F_XY_System(50.0);
+ AMOEBA amoebaLoad = new AMOEBA(tempFile.getAbsolutePath(), studiedSystem);
+ /*
+ * Improvement idea : defining equals on agent, and then test equality
+ */
+ assertEquals(amoeba.getAgents().size(), amoebaLoad.getAgents().size());
+ }
+
+ @Test
+ public void testRequestSameAmoeba() throws IOException {
+ File tempFile = File.createTempFile("testSave", "xml");
+ tempFile.deleteOnExit();
+ Double[] requestOriginal = new Double[SIZE];
+ Double[] requestLoaded = new Double[SIZE];
+
+ amoeba.saver.save(tempFile);
+ for (int i = 0; i < test.length; i++) {
+ requestOriginal[i] = Round.round(amoeba.request(test[i]), ROUNDING_DECIMAL);
+ }
+
+ amoeba.saver.load(tempFile);
+ for (int i = 0; i < test.length; i++) {
+ requestLoaded[i] = Round.round(amoeba.request(test[i]), ROUNDING_DECIMAL);
+ }
+
+ assertArrayEquals(requestOriginal, requestLoaded);
+ }
+
+ @Test
+ public void testRequestDiffAmoeba() throws IOException {
+ File tempFile = File.createTempFile("testSave", "xml");
+ tempFile.deleteOnExit();
+ Double[] requestOriginal = new Double[SIZE];
+ Double[] requestLoaded = new Double[SIZE];
+
+ amoeba.saver.save(tempFile);
+ for (int i = 0; i < test.length; i++) {
+ requestOriginal[i] = Round.round(amoeba.request(test[i]), ROUNDING_DECIMAL);
+ }
+
+ StudiedSystem studiedSystem = new F_XY_System(50.0);
+ AMOEBA amoebaLoad = new AMOEBA(tempFile.getAbsolutePath(), studiedSystem);
+ amoebaLoad.saver.load(tempFile);
+ for (int i = 0; i < test.length; i++) {
+ requestLoaded[i] = Round.round(amoebaLoad.request(test[i]), ROUNDING_DECIMAL);
+ }
+
+ assertArrayEquals(requestOriginal, requestLoaded);
+ }
+
+ @Test
+ public void testRequestDiffAmoebaNew() throws IOException {
+ File tempFile = File.createTempFile("testSave", "xml");
+ tempFile.deleteOnExit();
+ Double[] requestLoaded1 = new Double[SIZE];
+ Double[] requestLoaded2 = new Double[SIZE];
+
+ amoeba.saver.save(tempFile);
+
+ AMOEBA amoebaLoad1 = new AMOEBA(tempFile.getAbsolutePath(), null);
+ amoebaLoad1.saver.load(tempFile);
+ for (int i = 0; i < test.length; i++) {
+ requestLoaded1[i] = Round.round(amoebaLoad1.request(test[i]), ROUNDING_DECIMAL);
+ }
+
+ AMOEBA amoebaLoad2 = new AMOEBA(tempFile.getAbsolutePath(), null);
+ amoebaLoad2.saver.load(tempFile);
+ for (int i = 0; i < test.length; i++) {
+ requestLoaded2[i] = Round.round(amoebaLoad2.request(test[i]), ROUNDING_DECIMAL);
+ }
+
+ assertArrayEquals(requestLoaded1, requestLoaded2);
+ }
+
+}
diff --git a/AMOEBAonAMAK/tests/utils/TestSetup.java b/AMOEBAonAMAK/tests/utils/TestSetup.java
new file mode 100644
index 0000000000000000000000000000000000000000..2a2342985dab7aa702dead9d1fbd25c8ff3469e1
--- /dev/null
+++ b/AMOEBAonAMAK/tests/utils/TestSetup.java
@@ -0,0 +1,61 @@
+package utils;
+
+import java.io.IOException;
+import java.nio.file.Paths;
+import java.util.HashMap;
+
+import org.junit.jupiter.api.AfterAll;
+import org.junit.jupiter.api.BeforeAll;
+import org.junit.jupiter.api.BeforeEach;
+
+import experiments.F_XY_System;
+import fr.irit.smac.amak.Configuration;
+import kernel.AMOEBA;
+import kernel.StudiedSystem;
+import kernel.backup.SaveHelperImpl;
+
+public class TestSetup {
+ protected AMOEBA amoeba;
+ /**
+ * Testing sample : increasing this number lead to slower test and more chance of failure.
+ */
+ public static final int SIZE = 50;
+ public static final int ROUNDING_DECIMAL = 5;
+ public static HashMap<String, Double>[] train = new HashMap[SIZE];
+ public static HashMap<String, Double>[] test = new HashMap[SIZE];
+
+ @BeforeAll
+ public static void setupTrainTestValues() {
+ StudiedSystem studiedSystem = new F_XY_System(50.0);
+ for (int i = 0; i < train.length; i++) {
+ studiedSystem.playOneStep();
+ train[i] = studiedSystem.getOutput();
+ }
+ for (int i = 0; i < test.length; i++) {
+ studiedSystem.playOneStep();
+ test[i] = studiedSystem.getOutput();
+ }
+ }
+
+ @BeforeEach
+ public void setup() {
+ Configuration.allowedSimultaneousAgentsExecution = 1;
+ Configuration.commandLineMode = true;
+ StudiedSystem studiedSystem = new F_XY_System(50.0);
+ amoeba = new AMOEBA("resources/twoDimensionsLauncher.xml", studiedSystem);
+ amoeba.saver.setAutoSave(false);
+ for (int i = 0; i < train.length; i++) {
+ studiedSystem.playOneStep();
+ amoeba.learn(train[i]);
+ }
+ }
+
+ @AfterAll
+ public static void clean() {
+ try {
+ DeleteDirectory.deleteDirectoryRecursion(Paths.get(SaveHelperImpl.savesRoot));
+ } catch (IOException e) {
+ e.printStackTrace();
+ }
+ }
+}
diff --git a/README.md b/README.md
index 1d608cdcdec651d4653af292d4b77633bdd4c896..f53d24a2fa7562aece206214c5727c58fbe7b41b 100644
--- a/README.md
+++ b/README.md
@@ -1,10 +1,15 @@
# AMAKFX and AMOEBAonAMAK
-Tested with openjdk 11.
+Tested with OpenJDK 11, should work with Java 8.
-## Build Jar with dependencies
+Check [the documentation directory](documentation) for more detailed and in depth instruction and explanation.
+
+Check AMAKFX's [README](AMAKFX/README.md) for more detail on how to use it.
+
+# Quick start :
+## Maven build Jar with dependencies
`mvn clean compile assembly:single`
-Note that the resulting jars are not platform independant.
+Note that the resulting jars are not platform independent.
## Use with Eclipse
Clone this repo and import it as a Maven project.
@@ -16,5 +21,13 @@ AMOEBA-parent
| AMAKFX
| AMOEBAonAMAK
```
-For more detail check the `documentation` directory.
+Check AMAKFX's [README](AMAKFX/README.md) for more detail on how to use it.
+
+Check [the documentation directory](documentation) for more detailed and in depth instruction and explanation on AMOEBA.
+
+### Amoeba Quick start
+```Java
+StudiedSystem studiedSystem = new F_XY_System(50.0);
+AMOEBA amoeba = new AMOEBA("resources/twoDimensionsLauncher.xml", studiedSystem);
+```
\ No newline at end of file
diff --git a/documentation/GUI_description.pdf b/documentation/GUI_description.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..0b3f72f7104237c4e91c88d76ca29f9c1dd0d728
Binary files /dev/null and b/documentation/GUI_description.pdf differ
diff --git a/documentation/GUI_description_1.jpg b/documentation/GUI_description_1.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..f43f90287ae52c1053b5f30c916b2d9a3b172320
Binary files /dev/null and b/documentation/GUI_description_1.jpg differ
diff --git a/documentation/GUI_description_2.jpg b/documentation/GUI_description_2.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..69d573416f07c978cff3173c1e19a8d136f57ede
Binary files /dev/null and b/documentation/GUI_description_2.jpg differ
diff --git a/documentation/gui.md b/documentation/gui.md
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..9e7084ec56fbd2f58616f3fc2f2d229391434175 100644
--- a/documentation/gui.md
+++ b/documentation/gui.md
@@ -0,0 +1,5 @@
+# GUI description
+[Hi-res pdf](GUI_description.pdf)
+
+
+
\ No newline at end of file
diff --git a/documentation/installing.md b/documentation/installing.md
index 874ec65c211c181136023daf4f41e16bc731dde4..f450f8488678a196019b3d14571c6b0ebdbb2dec 100644
--- a/documentation/installing.md
+++ b/documentation/installing.md
@@ -16,12 +16,33 @@ Compile and run tests :
Build an executable jar with all dependencies :
-`mvn clean compile assembly:single`
+```
+mvn clean compile assembly:single
+```
+
+You can change the main class of the executable jar with the argument `-Dmain.class=fully.qualified.Main`.
+
+Example :
+```
+mvn clean compile assembly:single -Dmain.class=ros.Main
+```
Results are in `target` folder.
You may have to tweak the `pom.xml` to make it compatible with your maven/java setup, or to chose the starting class of your executable jar.
+For example, if you use jdk-1.8 (java 8) you have to replace
+```
+<release>8</release>
+```
+in `maven-compiler-plugin` by
+```
+<source>1.8</source>
+<target>1.8</target>
+```
+
+The resulting jar is not platform agnostic.
+
### Build with eclipse
`File > Open project from file system`, select the folder `AMOEBA3`, eclipse should detect 3 maven projects :
```
@@ -33,4 +54,15 @@ AMOEBA-parent
Make sure it works by right-clicking on `AMOEBA-parent` > `Run as > Maven test`. You should get a `BUILD SUCCES`.
-Make sure it works with JavaFX : right-click on `AMAKFX.src.fr.irit.smac.amak.examples.philosophers.PhilosopherLaunchExample.java` or any other example and `Run as > Java application`. Do the same for `AMOEBAonAMAK.src.experiments.MinimalMain.java`. You should get a new window, and no error in the console.
\ No newline at end of file
+Make sure it works with JavaFX : right-click on `AMAKFX.src.fr.irit.smac.amak.examples.philosophers.PhilosopherLaunchExample.java` or any other example and `Run as > Java application`. Do the same for `AMOEBAonAMAK.src.experiments.MinimalMain.java`. You should get a new window, and no error in the console.
+
+## Troubleshooting
+ I get `Failed to execute goal org.apache.maven.plugins:maven-compiler-plugin:3.8.0:compile (default-compile) on project AMAKFX: Fatal error compiling: invalid flag: --release -> [Help 1]` ? In AMOEBA-parent's pom.xml, replace
+```
+<release>8</release>
+```
+in `maven-compiler-plugin` by
+```
+<source>1.8</source>
+<target>1.8</target>
+```
\ No newline at end of file
diff --git a/documentation/py4j.md b/documentation/py4j.md
new file mode 100644
index 0000000000000000000000000000000000000000..19bcf82b9b08de5529e3ee4f2f86fd0814728dd4
--- /dev/null
+++ b/documentation/py4j.md
@@ -0,0 +1,11 @@
+# Using Py4j
+[Py4j](https://www.py4j.org/) is a Python/Java tool allowing control java code with python.
+
+Demos are available in the [py4j_demo](py4j_demo) directory.
+
+A minimalistic main is provided at `py4j.Main.java`. Please note that py4j use socket, so only one process of that main can be executed at a given time. You can have multiple amoeba on a same process, but only one GUI on the same process. If you need to launch multiple amoebas with GUI at a same time, check py4j official documentation on how to change sockets.
+
+To compile AMOEBA as an executable jar with this main, do :
+```
+mvn clean compile assembly:single -Dmain.class=py4j.Main
+```
\ No newline at end of file
diff --git a/documentation/py4j_demo/.gitignore b/documentation/py4j_demo/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..aadc34dd54e8dd96b10c6b8c845a071837dc3340
--- /dev/null
+++ b/documentation/py4j_demo/.gitignore
@@ -0,0 +1,2 @@
+.idea/
+saves/
diff --git a/documentation/py4j_demo/README.md b/documentation/py4j_demo/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..65c3fe0dcd1f70cd60f98fb59a715da0c932044d
--- /dev/null
+++ b/documentation/py4j_demo/README.md
@@ -0,0 +1,32 @@
+Official py4j documentation [here](https://www.py4j.org/).
+
+# Install :
+Install python dependencies :
+```
+pip3 install requirements.txt
+```
+Optional : check [openai gym](https://gym.openai.com/) documentation for a full install.
+
+Run the setup script [setup.sh](setup.sh) (linux only). It just clean some file, compile the correct AMOEBAonAMAK jar and copy it for ease of use.
+
+You're good to go, check that py4j is correctly working with [basic_demo.py](basic_demo.py) :
+```
+python3 basic_demo.py
+```
+You should get the classic amoeba's GUI, and random context appearing.
+
+Then you can look at some actual learning, inside [learn_gym.py](learn_gym.py).
+
+
+# Optional : Ros2Learn
+[Ros2Learn](https://github.com/AcutronicRobotics/ros2learn) provide some tools for machine learning on robots, using Ros2, openAI gym, and gazebo.
+
+Install Ros2 and Ros2learn, follow Ros2Learn instruction. Make sure your version of gazebo is at least 9.9.
+
+In your python script, import gym_gazebo2. Before running your python code make sure that you properly loaded Ros2 and Ros2learn environment using their provision scripts.
+
+You can now use gym environment provided by Ros2learn as regular gym environment.
+```Python
+env = gym.make('MARA-v0')
+```
+
diff --git a/documentation/py4j_demo/basic_demo.py b/documentation/py4j_demo/basic_demo.py
new file mode 100644
index 0000000000000000000000000000000000000000..f4cf2a4f505216c79511ccf5cd18d3d798c0dcd5
--- /dev/null
+++ b/documentation/py4j_demo/basic_demo.py
@@ -0,0 +1,17 @@
+import subprocess
+import time
+
+from py4j.java_gateway import JavaGateway, GatewayParameters
+
+if __name__ == '__main__':
+ # Make sure to run setup.sh at least once before running this script
+
+ subprocess.Popen(["java", "-jar", "amoeba.jar"])
+ time.sleep(2)
+
+ gateway = JavaGateway(gateway_parameters=GatewayParameters(auto_convert=True))
+ amoeba = gateway.jvm.kernel.AMOEBA("/home/daavve/AMOEBA3/AMOEBAonAMAK/resources/twoDimensionsLauncher.xml", None)
+ for i in range(100):
+ amoeba.learn({"px0": float(i), "px1": float(i), "oracle": float(i)})
+ print(i, " ", amoeba.getAction())
+
diff --git a/documentation/py4j_demo/cartpole_trained.xml b/documentation/py4j_demo/cartpole_trained.xml
new file mode 100644
index 0000000000000000000000000000000000000000..fcde61a6c4fcc58cf92b81e16f0bfc06d4dcd11f
--- /dev/null
+++ b/documentation/py4j_demo/cartpole_trained.xml
@@ -0,0 +1,168652 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<System>
+ <Configuration>
+ <Learning creationOfNewContext="true" loadPresetContext="true" />
+ <Data><?xml version="1.0" encoding="UTF-8"?>
+<java version="11.0.3" class="java.beans.XMLDecoder">
+ <object class="kernel.AmoebaData" id="AmoebaData0">
+ <void class="kernel.AmoebaData" method="getField">
+ <string>prediction</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>155.8727816378232</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>endogenousPredictionActivatedContextsOverlaps</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>-11.745508587337099</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>endogenousPredictionActivatedContextsOverlapsWorstDimInfluence</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>-11.745508587337099</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>endogenousPredictionActivatedContextsOverlapsInfluenceWithoutConfidence</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>-11.745508587337099</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithoutConfidence</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>-11.745508587337099</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>endogenousPredictionActivatedContextsOverlapsWorstDimInfluenceWithVolume</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>-11.745508587337099</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>endogenousPredictionActivatedContextsSharedIncompetence</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>-11.745508587337099</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>endogenousPredictionNContexts</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>NaN</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>endogenousPredictionNContextsByInfluence</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>-11.745508587337099</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>oracleValue</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>155.0</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>oldOracleValue</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>155.0</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>criticity</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.8727816378232092</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>distanceToRegression</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.001463500520720902</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>spatialGeneralizationScore</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>21.262580152858632</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>noCreation</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <boolean>false</boolean>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>firstContext</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <void class="kernel.AmoebaData" id="Field0" method="getField">
+ <string>useOracle</string>
+ <void id="Boolean0" method="get">
+ <object idref="AmoebaData0"/>
+ </void>
+ </void>
+ <object idref="Boolean0"/>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>newContextWasCreated</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <object idref="Boolean0"/>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>contextFromPropositionWasSelected</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <object idref="Boolean0"/>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>activeLearning</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <object idref="Boolean0"/>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>selfRequest</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <object class="java.util.HashMap">
+ <void method="put">
+ <string>p0</string>
+ <double>8.14058066494322</double>
+ </void>
+ <void method="put">
+ <string>a1</string>
+ <double>0.002713337946432266</double>
+ </void>
+ <void method="put">
+ <string>p1</string>
+ <double>109.45759734947954</double>
+ </void>
+ <void method="put">
+ <string>p2</string>
+ <double>-1.8134547865036947</double>
+ </void>
+ <void method="put">
+ <string>p3</string>
+ <double>-126.03352957103412</double>
+ </void>
+ <void method="put">
+ <string>a0</string>
+ <double>0.9817879501267666</double>
+ </void>
+ </object>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>maxConfidence</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>7.0</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>minConfidence</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>-32.0</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>maxPrediction</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>155.0</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>normalizedCriticality</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.03934783179969776</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>noBestContext</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <object idref="Boolean0"/>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>evolutionCriticalityPrediction</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.20889538548053246</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>evolutionCriticalityMapping</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.7442478522388146</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>evolutionCriticalityConfidence</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <double>0.20889538548053246</double>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>currentCriticalityMapping</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <int>1</int>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>contextSelfAnalisisExecutionTime</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <long>4</long>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>create_New_ContextNCSExecutionTime</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <long>1562067289302</long>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>otherExecutionTime</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <long>86</long>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>playExecutionTimeSum</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <long>182</long>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>contextSelfAnalisisExecutionTimeSum</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <long>42918</long>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>incompetentHeadNCSExecutionTimeSum</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <long>8094</long>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>concurrenceNCSExecutionTimeSum</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <long>66</long>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>create_New_ContextNCSExecutionTimeSum</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <long>255029</long>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>otherExecutionTimeSum</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <long>267428</long>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>predictionPerformance</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <object class="agents.head.DynamicPerformance" id="DynamicPerformance0">
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>successesBeforeDiminution</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <void class="kernel.AmoebaData" id="Field1" method="getField">
+ <string>numberOfPointsForRegression</string>
+ <void id="Integer0" method="get">
+ <object idref="AmoebaData0"/>
+ </void>
+ </void>
+ <object idref="Integer0"/>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>conflictsBeforeAugmentation</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <object idref="Integer0"/>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>performanceIndicator</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <double>0.6571325790667084</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>performanceCounter</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <int>-16</int>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>augmentationFactor</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <double>0.5</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>diminutionFactor</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <double>0.5</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>minPerformanceIndicator</string>
+ <void method="set">
+ <object idref="DynamicPerformance0"/>
+ <double>0.01</double>
+ </void>
+ </void>
+ </object>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>regressionPerformance</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <object class="agents.head.DynamicPerformance" id="DynamicPerformance1">
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>successesBeforeDiminution</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <void class="kernel.AmoebaData" id="Field2" method="getField">
+ <string>numberOfCriticityValuesForAverage</string>
+ <void id="Integer1" method="get">
+ <object idref="AmoebaData0"/>
+ </void>
+ </void>
+ <object idref="Integer1"/>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>conflictsBeforeAugmentation</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <object idref="Integer1"/>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>performanceIndicator</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <double>1.0</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>performanceCounter</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <int>46</int>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>augmentationFactor</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <double>0.5</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>diminutionFactor</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <double>0.5</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>minPerformanceIndicator</string>
+ <void method="set">
+ <object idref="DynamicPerformance1"/>
+ <double>1.0</double>
+ </void>
+ </void>
+ </object>
+ </void>
+ </void>
+ <void class="kernel.AmoebaData" method="getField">
+ <string>mappingPerformance</string>
+ <void method="set">
+ <object idref="AmoebaData0"/>
+ <object class="agents.head.DynamicPerformance" id="DynamicPerformance2">
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>successesBeforeDiminution</string>
+ <void method="set">
+ <object idref="DynamicPerformance2"/>
+ <int>100000</int>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>conflictsBeforeAugmentation</string>
+ <void method="set">
+ <object idref="DynamicPerformance2"/>
+ <int>1000000</int>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>performanceIndicator</string>
+ <void method="set">
+ <object idref="DynamicPerformance2"/>
+ <double>0.04</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>augmentationFactor</string>
+ <void method="set">
+ <object idref="DynamicPerformance2"/>
+ <double>1.1</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>diminutionFactor</string>
+ <void method="set">
+ <object idref="DynamicPerformance2"/>
+ <double>0.9</double>
+ </void>
+ </void>
+ <void class="agents.head.DynamicPerformance" method="getField">
+ <string>minPerformanceIndicator</string>
+ <void method="set">
+ <object idref="DynamicPerformance2"/>
+ <double>1.0</double>
+ </void>
+ </void>
+ </object>
+ </void>
+ </void>
+ </object>
+</java></Data>
+ </Configuration>
+ <StartingAgents>
+ <Controller Name="Controller">
+ <ErrorMargin ErrorAllowed="0.6571325790667084" AugmentationFactorError="0.5" DiminutionFactorError="0.5" MinErrorAllowed="0.01" NConflictBeforeAugmentation="50" NSuccessBeforeDiminution="50" />
+ </Controller>
+ <Sensor Name="p0" Enum="false" Max="62.38221152209407" Min="-47.48873252999115" />
+ <Sensor Name="p1" Enum="false" Max="246.08201823161943" Min="-284.31853349389627" />
+ <Sensor Name="p2" Enum="false" Max="20.905982654560233" Min="-20.902201064692274" />
+ <Sensor Name="p3" Enum="false" Max="306.2945480650874" Min="-311.0322111647933" />
+ <Sensor Name="a0" Enum="true" Max="1.0" Min="0.0" />
+ <Sensor Name="a1" Enum="true" Max="1.0" Min="0.0" />
+ </StartingAgents>
+ <PresetContexts>
+ <LastPerceptionsAndActionState p0="-5.654485955285741" a1="1.0" p1="0.3340006922370714" p2="0.42127323781161297" p3="-2.5314347293027173" oracle="155.0" a0="0.0" />
+ <!-- Nb contexts = 1732 -->
+ <Context Name="2042226795" Confidence="3.0" ActionsProposal="178.93804147102097" Activated="false">
+ <Ranges>
+ <Range Sensor="p1" Start="48.40000650369974" End="69.80476610782823" />
+ <Range Sensor="a1" Start="0.96" End="1.0" />
+ <Range Sensor="p3" Start="-105.60539328381513" End="-76.40910569182303" />
+ <Range Sensor="p0" Start="3.7338681896116785" End="6.090954200339412" />
+ <Range Sensor="a0" Start="0.0" End="0.04" />
+ <Range Sensor="p2" Start="-4.696068309648567" End="-1.5310970116390377" />
+ </Ranges>
+ <LocalModel Type="MILLER_REGRESSION">
+ <Coefs>
+ <Value v="63.161991385608076" />
+ <Value v="-21.744821368054616" />
+ <Value v="3.0959980751411362" />
+ <Value v="-8.51936705437516" />
+ <Value v="1.826956486009302" />
+ <Value v="-0.0" />
+ <Value v="0.0" />
+ </Coefs>
+ <Experiments>
+ <Experiment Proposition="37.0">
+ <Values>
+ <Value Sensor="p0" Value="0.5077969305123753" />
+ <Value Sensor="p1" Value="0.21593920944191214" />
+ <Value Sensor="p2" Value="-0.9936985695929382" />
+ <Value Sensor="p3" Value="-14.007812522397034" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="13.0">
+ <Values>
+ <Value Sensor="p0" Value="2.355240173840224" />
+ <Value Sensor="p1" Value="2.6299067348138845" />
+ <Value Sensor="p2" Value="0.06798080416080127" />
+ <Value Sensor="p3" Value="-1.4946172594699194" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="13.0">
+ <Values>
+ <Value Sensor="p0" Value="2.850660833894356" />
+ <Value Sensor="p1" Value="2.6283886205905436" />
+ <Value Sensor="p2" Value="-0.576740609859264" />
+ <Value Sensor="p3" Value="-1.4611510869928013" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="13.0">
+ <Values>
+ <Value Sensor="p0" Value="3.3991107153544697" />
+ <Value Sensor="p1" Value="22.174833587079434" />
+ <Value Sensor="p2" Value="-1.2608662608381764" />
+ <Value Sensor="p3" Value="-31.486286798918524" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="13.0">
+ <Values>
+ <Value Sensor="p0" Value="3.8426073870960584" />
+ <Value Sensor="p1" Value="41.70476034033568" />
+ <Value Sensor="p2" Value="-1.8905919968165468" />
+ <Value Sensor="p3" Value="-61.14953319136278" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="13.0">
+ <Values>
+ <Value Sensor="p0" Value="4.676702593902772" />
+ <Value Sensor="p1" Value="61.242862266176836" />
+ <Value Sensor="p2" Value="-3.1135826606438024" />
+ <Value Sensor="p3" Value="-91.00724948781908" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="12.0">
+ <Values>
+ <Value Sensor="p0" Value="3.869392025429994" />
+ <Value Sensor="p1" Value="53.74339635948622" />
+ <Value Sensor="p2" Value="-4.062761415758476" />
+ <Value Sensor="p3" Value="-90.77331243399105" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="33.0">
+ <Values>
+ <Value Sensor="p0" Value="4.75624287271545" />
+ <Value Sensor="p1" Value="63.0944890321364" />
+ <Value Sensor="p2" Value="-3.5520839233815797" />
+ <Value Sensor="p3" Value="-83.24887364580503" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ </Experiments>
+ </LocalModel>
+ </Context>
+ <Context Name="1318363612" Confidence="2.0" ActionsProposal="-150.90176209058046" Activated="false">
+ <Ranges>
+ <Range Sensor="p1" Start="41.99634099460496" End="80.79577987055931" />
+ <Range Sensor="a1" Start="0.96" End="1.0" />
+ <Range Sensor="p3" Start="-135.83579971424476" End="-84.74229642825858" />
+ <Range Sensor="p0" Start="1.6588050199163888" End="7.315811445662948" />
+ <Range Sensor="a0" Start="0.0" End="0.04" />
+ <Range Sensor="p2" Start="-6.516213299404948" End="-3.351242001395419" />
+ </Ranges>
+ <LocalModel Type="MILLER_REGRESSION">
+ <Coefs>
+ <Value v="-32.46107313844982" />
+ <Value v="24.200464999949503" />
+ <Value v="-8.303356474947497" />
+ <Value v="17.572350570425957" />
+ <Value v="-5.440024240728015" />
+ <Value v="-0.0" />
+ <Value v="0.0" />
+ </Coefs>
+ <Experiments>
+ <Experiment Proposition="37.0">
+ <Values>
+ <Value Sensor="p0" Value="0.5077969305123753" />
+ <Value Sensor="p1" Value="0.21593920944191214" />
+ <Value Sensor="p2" Value="-0.9936985695929382" />
+ <Value Sensor="p3" Value="-14.007812522397034" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="13.0">
+ <Values>
+ <Value Sensor="p0" Value="2.355240173840224" />
+ <Value Sensor="p1" Value="2.6299067348138845" />
+ <Value Sensor="p2" Value="0.06798080416080127" />
+ <Value Sensor="p3" Value="-1.4946172594699194" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="13.0">
+ <Values>
+ <Value Sensor="p0" Value="2.850660833894356" />
+ <Value Sensor="p1" Value="2.6283886205905436" />
+ <Value Sensor="p2" Value="-0.576740609859264" />
+ <Value Sensor="p3" Value="-1.4611510869928013" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="13.0">
+ <Values>
+ <Value Sensor="p0" Value="3.3991107153544697" />
+ <Value Sensor="p1" Value="22.174833587079434" />
+ <Value Sensor="p2" Value="-1.2608662608381764" />
+ <Value Sensor="p3" Value="-31.486286798918524" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="13.0">
+ <Values>
+ <Value Sensor="p0" Value="3.8426073870960584" />
+ <Value Sensor="p1" Value="41.70476034033568" />
+ <Value Sensor="p2" Value="-1.8905919968165468" />
+ <Value Sensor="p3" Value="-61.14953319136278" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="13.0">
+ <Values>
+ <Value Sensor="p0" Value="4.676702593902772" />
+ <Value Sensor="p1" Value="61.242862266176836" />
+ <Value Sensor="p2" Value="-3.1135826606438024" />
+ <Value Sensor="p3" Value="-91.00724948781908" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="13.0">
+ <Values>
+ <Value Sensor="p0" Value="5.901559839226309" />
+ <Value Sensor="p1" Value="80.79577987055931" />
+ <Value Sensor="p2" Value="-4.933727650400184" />
+ <Value Sensor="p3" Value="-121.2376559182487" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
+ </Experiment>
+ <Experiment Proposition="12.0">
+ <Values>
+ <Value Sensor="p0" Value="3.471640597427835" />
+ <Value Sensor="p1" Value="54.045236683109124" />
+ <Value Sensor="p2" Value="-4.987140135799937" />
+ <Value Sensor="p3" Value="-91.3886683841928" />
+ <Value Sensor="a0" Value="0.0" />
+ <Value Sensor="a1" Value="1.0" />
+ </Values>
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+ </PresetContexts>
+</System>
diff --git a/documentation/py4j_demo/clean.sh b/documentation/py4j_demo/clean.sh
new file mode 100755
index 0000000000000000000000000000000000000000..a11acd9cdbaad95c8d86ab61a64a32147d42aa4d
--- /dev/null
+++ b/documentation/py4j_demo/clean.sh
@@ -0,0 +1,6 @@
+#!/bin/sh
+
+rm amoeba.jar
+rm ./*.log
+rm -R ./saves/
+
diff --git a/documentation/py4j_demo/config.xml b/documentation/py4j_demo/config.xml
new file mode 100644
index 0000000000000000000000000000000000000000..9a3e10b099e120c9290fee7aa1906c4aed421d65
--- /dev/null
+++ b/documentation/py4j_demo/config.xml
@@ -0,0 +1,21 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<System>
+
+ <Configuration>
+ <Learning allowed = "true" creationOfNewContext = "true" loadPresetContext = "false"></Learning>
+ </Configuration>
+
+ <StartingAgents>
+ <Sensor Name="p0" Enum="false" />
+ <Sensor Name="p1" Enum="false" />
+ <Sensor Name="p2" Enum="false" />
+ <Sensor Name="p3" Enum="false" />
+ <Sensor Name="a0" Enum="true" />
+
+ <Controller Name="Controller">
+ <ErrorMargin ErrorAllowed="2000.0" AugmentationFactorError="5.0" DiminutionFactorError="0.4" MinErrorAllowed="0.1" NConflictBeforeAugmentation="40" NSuccessBeforeDiminution="80" />
+
+ </Controller>
+ </StartingAgents>
+
+</System>
diff --git a/documentation/py4j_demo/learn_gym.py b/documentation/py4j_demo/learn_gym.py
new file mode 100644
index 0000000000000000000000000000000000000000..ffc206c3186b3bcdc945bb21e877a2d40d82e764
--- /dev/null
+++ b/documentation/py4j_demo/learn_gym.py
@@ -0,0 +1,214 @@
+import os
+import gym
+#import gym_gazebo2
+import subprocess
+import time
+import math
+import numpy as np
+import matplotlib.pyplot as plt
+
+from py4j.java_gateway import JavaGateway, GatewayParameters, set_field
+
+MULTIPLICATOR = 1000.0
+
+def gen_file(percepts:list):
+ """
+ Create the config file for amoeba
+ :param percepts: list of tuple (percept:string, enum:bool)
+ :return config file name
+ """
+ filename = "config.xml"
+ with open(filename, "w") as xmlFile:
+ start = """<?xml version="1.0" encoding="UTF-8"?>
+<System>
+
+ <Configuration>
+ <Learning allowed = "true" creationOfNewContext = "true" loadPresetContext = "false"></Learning>
+ </Configuration>
+
+ <StartingAgents>
+"""
+ xmlFile.write(start)
+ for percept, enum in percepts:
+ xmlFile.write("\t\t<Sensor Name=\"%s\" Enum=\"%s\" />\n" % (percept, "true" if enum else "false"))
+ end = """
+ <Controller Name="Controller">
+ <ErrorMargin ErrorAllowed="2000.0" AugmentationFactorError="5.0" DiminutionFactorError="0.4" MinErrorAllowed="0.1" NConflictBeforeAugmentation="40" NSuccessBeforeDiminution="80" />
+
+ </Controller>
+ </StartingAgents>
+
+</System>
+"""
+ xmlFile.write(end)
+ return os.path.realpath(xmlFile.name)
+
+
+def percepts_from_env(env) -> list:
+ percepts = []
+ for i in range(env.observation_space.shape[0]):
+ percepts.append(("p%d" % i, False))
+ if isinstance(env.action_space, gym.spaces.discrete.Discrete):
+ n = 1
+ enum = True
+ else:
+ n = env.action_space.shape[0]
+ enum = False
+ for i in range(n):
+ percepts.append(("a%d" % i, enum))
+ return percepts
+
+
+def msg_obj(obs:list, act:list, oracle) -> dict:
+ msg = dict()
+ for i, o in enumerate(obs):
+ msg["p%d" % i] = float(o*MULTIPLICATOR)
+ for i, a in enumerate(act):
+ msg["a%d" % i] = float(a*MULTIPLICATOR)
+ msg["oracle"] = float(oracle)
+ return msg
+
+
+def chose_next_action(amoeba, state, env):
+ if isinstance(env.action_space, gym.spaces.discrete.Discrete):
+ # Special case for Discrete, work better than maximize
+ #proposition = []
+ #for i in range(env.action_space.n):
+ # act = [i]
+ # proposition.append(amoeba.request(msg_obj(state, act, 0)))
+ #return np.argmax(proposition)
+ # ----------------------------------------------------
+ n = 1
+ else:
+ n = env.action_space.shape[0]
+
+ action = [0.0]*n
+ msg = msg_obj(state, [], 0)
+ msg.pop("oracle", None)
+ res = amoeba.maximize(msg)
+
+ if (res["oracle"] == -math.inf) or (res is None):
+ return random_action()
+
+ for i in range(n):
+ action[i] = res["a%d" % i]/MULTIPLICATOR
+
+ if isinstance(env.action_space, gym.spaces.discrete.Discrete) :
+ return int(round(action[0]))
+ else:
+ return action
+
+
+def learn_amoeba(amoeba, state, action, reward, env):
+ if isinstance(env.action_space, gym.spaces.discrete.Discrete):
+ act = [action]
+ amoeba.learn(msg_obj(state, act, reward))
+ else:
+ amoeba.learn(msg_obj(state, action, reward))
+
+
+def random_action():
+ #nb_random_action += 1
+ return env.action_space.sample()
+
+
+def render():
+ if i > 0:
+ env.render()
+
+
+if __name__ == '__main__':
+
+ plt.ion()
+
+ # Make sure to run setup.sh at least once before running this script
+ subprocess.Popen(["java", "-jar", "amoeba.jar"])
+ time.sleep(2)
+
+ gateway = JavaGateway(gateway_parameters=GatewayParameters(auto_convert=True, auto_field=True))
+ #gateway.jvm.py4j.Main.Control.setComandLine(True)
+ gateway.jvm.py4j.Main.Control.setLogLevel("INFORM")
+
+ env = gym.make('CartPole-v0')
+ env.reset()
+ percepts = percepts_from_env(env)
+ filename = gen_file(percepts_from_env(env))
+
+ amoeba = gateway.jvm.kernel.AMOEBA()
+ backup_sys = gateway.jvm.kernel.backup.BackupSystem(amoeba)
+ file = gateway.jvm.java.io.File(filename)
+ backup_sys.load(file)
+
+ # Initialize variables to track rewards
+ reward_list = []
+ ave_reward_list = []
+ nb_random_action = 0
+
+ episodes = 1000
+ epsilon = 0.3
+ min_eps = 0.02
+ reduction = 0.01
+ for i in range(episodes):
+ # Initialize parameters
+ done = False
+ tot_reward, reward = 0, 0
+ nb_random_action = 0
+ state = env.reset()
+ render()
+
+ state_action_list = []
+
+ j = 0
+ while not done:
+
+ if np.random.random() < 1 - epsilon:
+ action = chose_next_action(amoeba, state, env)
+ else:
+ action = random_action()
+
+ state_action_list.append((state, action))
+
+ reward = 0
+ # Get next state and reward
+ # j += 1
+ # if j >= 200:
+ # done = True
+ # r = -100
+ # else:
+ state2, r, done, info = env.step(action)
+ render()
+ reward += r
+
+ learn_amoeba(amoeba, state, action, reward, env)
+
+ tot_reward += reward
+
+ state = state2
+
+ # for state, action in state_action_list:
+ # learn_amoeba(amoeba, state, action, tot_reward, env)
+ print('Episode {} Reward: {} Random actions: {}/{} Info: {}'.format(i + 1, tot_reward, nb_random_action, i, info))
+
+ # Decay epsilon
+ if epsilon > min_eps:
+ epsilon -= reduction
+
+ # Track rewards
+ reward_list.append(tot_reward)
+
+ print_delta = 10
+ if (i + 1) % print_delta == 0:
+ ave_reward = np.mean(reward_list)
+ ave_reward_list.append(ave_reward)
+ reward_list = []
+ print(
+ 'Episode {}-{} Average Reward: {} Epsilon: {}'.format(i - print_delta + 1, i + 1, ave_reward, epsilon))
+ plt.clf()
+ plt.plot(ave_reward_list)
+ plt.pause(0.1)
+
+ plt.show()
+ plt.pause(100000)
+ env.close()
+
+
diff --git a/documentation/py4j_demo/requirements.txt b/documentation/py4j_demo/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9b4cb9d679796566de0f7d7b632057a6e2b547d2
--- /dev/null
+++ b/documentation/py4j_demo/requirements.txt
@@ -0,0 +1,4 @@
+py4j==0.10.8.1
+gym
+numpy
+matplotlib
diff --git a/documentation/py4j_demo/setup.sh b/documentation/py4j_demo/setup.sh
new file mode 100755
index 0000000000000000000000000000000000000000..2f4285d25255c87cb07b869a215c7f78f16fef8b
--- /dev/null
+++ b/documentation/py4j_demo/setup.sh
@@ -0,0 +1,5 @@
+#!/bin/sh
+
+sh clean.sh
+(cd ../.. && mvn clean compile assembly:single -Dmain.class=py4j.Main && cp AMOEBAonAMAK/target/AMOEBAonAMAK-1.0-jar-with-dependencies.jar documentation/py4j_demo/amoeba.jar)
+echo "Done. If there's no error."
diff --git a/documentation/ros_demo/.gitignore b/documentation/ros_demo/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..62527a1d2c4a08d1530e59ea693a29c404fdec7d
--- /dev/null
+++ b/documentation/ros_demo/.gitignore
@@ -0,0 +1,5 @@
+/catkin_ws/build/
+/catkin_ws/devel/
+/catkin_ws/install/
+
+!*.launch
diff --git a/documentation/ros_demo/Amoeba_ros_demo.xml b/documentation/ros_demo/Amoeba_ros_demo.xml
new file mode 100644
index 0000000000000000000000000000000000000000..cdebe78bb7c5b3706de6ecd1d8af4cff130dbb2e
--- /dev/null
+++ b/documentation/ros_demo/Amoeba_ros_demo.xml
@@ -0,0 +1,21 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<System>
+
+ <Configuration>
+ <Learning allowed = "true" creationOfNewContext = "true" loadPresetContext = "false"></Learning>
+ </Configuration>
+
+ <StartingAgents>
+ <Sensor Name="px" Enum="false" />
+ <Sensor Name="py" Enum="false" />
+ <Sensor Name="theta" Enum="false" />
+ <Sensor Name="prev_lin" Enum="false" />
+ <Sensor Name="prev_ang" Enum="false" />
+
+ <Controller Name="Controller">
+ <ErrorMargin ErrorAllowed="2000.0" AugmentationFactorError="5.0" DiminutionFactorError="0.4" MinErrorAllowed="0.1" NConflictBeforeAugmentation="40" NSuccessBeforeDiminution="80" />
+
+ </Controller>
+ </StartingAgents>
+
+</System>
diff --git a/documentation/ros_demo/catkin_ws/.catkin_workspace b/documentation/ros_demo/catkin_ws/.catkin_workspace
new file mode 100644
index 0000000000000000000000000000000000000000..52fd97e7ea4bd421af3f7dacb539d241bcee6583
--- /dev/null
+++ b/documentation/ros_demo/catkin_ws/.catkin_workspace
@@ -0,0 +1 @@
+# This file currently only serves to mark the location of a catkin workspace for tool integration
diff --git a/documentation/ros_demo/catkin_ws/src/CMakeLists.txt b/documentation/ros_demo/catkin_ws/src/CMakeLists.txt
new file mode 120000
index 0000000000000000000000000000000000000000..66dd650aca8bc895ebfd0001a46559de60baee2c
--- /dev/null
+++ b/documentation/ros_demo/catkin_ws/src/CMakeLists.txt
@@ -0,0 +1 @@
+/opt/ros/melodic/share/catkin/cmake/toplevel.cmake
\ No newline at end of file
diff --git a/documentation/ros_demo/catkin_ws/src/amoeba_demo/CMakeLists.txt b/documentation/ros_demo/catkin_ws/src/amoeba_demo/CMakeLists.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b5a34381e749c401660bd1f563079cb5de2e470a
--- /dev/null
+++ b/documentation/ros_demo/catkin_ws/src/amoeba_demo/CMakeLists.txt
@@ -0,0 +1,198 @@
+cmake_minimum_required(VERSION 2.8.3)
+project(amoeba_demo)
+
+## Compile as C++11, supported in ROS Kinetic and newer
+# add_compile_options(-std=c++11)
+
+## Find catkin macros and libraries
+## if COMPONENTS list like find_package(catkin REQUIRED COMPONENTS xyz)
+## is used, also find other catkin packages
+find_package(catkin REQUIRED COMPONENTS
+ roscpp
+ rospy
+ std_msgs
+ message_generation
+)
+
+## System dependencies are found with CMake's conventions
+# find_package(Boost REQUIRED COMPONENTS system)
+
+
+## Uncomment this if the package has a setup.py. This macro ensures
+## modules and global scripts declared therein get installed
+## See http://ros.org/doc/api/catkin/html/user_guide/setup_dot_py.html
+# catkin_python_setup()
+
+################################################
+## Declare ROS messages, services and actions ##
+################################################
+
+## To declare and build messages, services or actions from within this
+## package, follow these steps:
+## * Let MSG_DEP_SET be the set of packages whose message types you use in
+## your messages/services/actions (e.g. std_msgs, actionlib_msgs, ...).
+## * In the file package.xml:
+## * add a build_depend tag for "message_generation"
+## * add a build_depend and a exec_depend tag for each package in MSG_DEP_SET
+## * If MSG_DEP_SET isn't empty the following dependency has been pulled in
+## but can be declared for certainty nonetheless:
+## * add a exec_depend tag for "message_runtime"
+## * In this file (CMakeLists.txt):
+## * add "message_generation" and every package in MSG_DEP_SET to
+## find_package(catkin REQUIRED COMPONENTS ...)
+## * add "message_runtime" and every package in MSG_DEP_SET to
+## catkin_package(CATKIN_DEPENDS ...)
+## * uncomment the add_*_files sections below as needed
+## and list every .msg/.srv/.action file to be processed
+## * uncomment the generate_messages entry below
+## * add every package in MSG_DEP_SET to generate_messages(DEPENDENCIES ...)
+
+## Generate messages in the 'msg' folder
+add_message_files(
+ FILES
+ Amoeba_msg.msg
+)
+
+## Generate services in the 'srv' folder
+# add_service_files(
+# FILES
+# Service1.srv
+# Service2.srv
+# )
+
+## Generate actions in the 'action' folder
+# add_action_files(
+# FILES
+# Action1.action
+# Action2.action
+# )
+
+## Generate added messages and services with any dependencies listed here
+generate_messages(
+ DEPENDENCIES
+)
+
+################################################
+## Declare ROS dynamic reconfigure parameters ##
+################################################
+
+## To declare and build dynamic reconfigure parameters within this
+## package, follow these steps:
+## * In the file package.xml:
+## * add a build_depend and a exec_depend tag for "dynamic_reconfigure"
+## * In this file (CMakeLists.txt):
+## * add "dynamic_reconfigure" to
+## find_package(catkin REQUIRED COMPONENTS ...)
+## * uncomment the "generate_dynamic_reconfigure_options" section below
+## and list every .cfg file to be processed
+
+## Generate dynamic reconfigure parameters in the 'cfg' folder
+# generate_dynamic_reconfigure_options(
+# cfg/DynReconf1.cfg
+# cfg/DynReconf2.cfg
+# )
+
+###################################
+## catkin specific configuration ##
+###################################
+## The catkin_package macro generates cmake config files for your package
+## Declare things to be passed to dependent projects
+## INCLUDE_DIRS: uncomment this if your package contains header files
+## LIBRARIES: libraries you create in this project that dependent projects also need
+## CATKIN_DEPENDS: catkin_packages dependent projects also need
+## DEPENDS: system dependencies of this project that dependent projects also need
+catkin_package(
+# INCLUDE_DIRS include
+# LIBRARIES amoeba_demo
+# CATKIN_DEPENDS roscpp rospy std_msgs
+# DEPENDS system_lib
+)
+
+###########
+## Build ##
+###########
+
+## Specify additional locations of header files
+## Your package locations should be listed before other locations
+include_directories(
+# include
+ ${catkin_INCLUDE_DIRS}
+)
+
+## Declare a C++ library
+# add_library(${PROJECT_NAME}
+# src/${PROJECT_NAME}/amoeba_demo.cpp
+# )
+
+## Add cmake target dependencies of the library
+## as an example, code may need to be generated before libraries
+## either from message generation or dynamic reconfigure
+# add_dependencies(${PROJECT_NAME} ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
+
+## Declare a C++ executable
+## With catkin_make all packages are built within a single CMake context
+## The recommended prefix ensures that target names across packages don't collide
+# add_executable(${PROJECT_NAME}_node src/amoeba_demo_node.cpp)
+
+## Rename C++ executable without prefix
+## The above recommended prefix causes long target names, the following renames the
+## target back to the shorter version for ease of user use
+## e.g. "rosrun someones_pkg node" instead of "rosrun someones_pkg someones_pkg_node"
+# set_target_properties(${PROJECT_NAME}_node PROPERTIES OUTPUT_NAME node PREFIX "")
+
+## Add cmake target dependencies of the executable
+## same as for the library above
+# add_dependencies(${PROJECT_NAME}_node ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
+
+## Specify libraries to link a library or executable target against
+# target_link_libraries(${PROJECT_NAME}_node
+# ${catkin_LIBRARIES}
+# )
+
+#############
+## Install ##
+#############
+
+# all install targets should use catkin DESTINATION variables
+# See http://ros.org/doc/api/catkin/html/adv_user_guide/variables.html
+
+## Mark executable scripts (Python etc.) for installation
+## in contrast to setup.py, you can choose the destination
+# install(PROGRAMS
+# scripts/my_python_script
+# DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
+# )
+
+## Mark executables and/or libraries for installation
+# install(TARGETS ${PROJECT_NAME} ${PROJECT_NAME}_node
+# ARCHIVE DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
+# LIBRARY DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
+# RUNTIME DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
+# )
+
+## Mark cpp header files for installation
+# install(DIRECTORY include/${PROJECT_NAME}/
+# DESTINATION ${CATKIN_PACKAGE_INCLUDE_DESTINATION}
+# FILES_MATCHING PATTERN "*.h"
+# PATTERN ".svn" EXCLUDE
+# )
+
+## Mark other files for installation (e.g. launch and bag files, etc.)
+# install(FILES
+# # myfile1
+# # myfile2
+# DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
+# )
+
+#############
+## Testing ##
+#############
+
+## Add gtest based cpp test target and link libraries
+# catkin_add_gtest(${PROJECT_NAME}-test test/test_amoeba_demo.cpp)
+# if(TARGET ${PROJECT_NAME}-test)
+# target_link_libraries(${PROJECT_NAME}-test ${PROJECT_NAME})
+# endif()
+
+## Add folders to be run by python nosetests
+# catkin_add_nosetests(test)
diff --git a/documentation/ros_demo/catkin_ws/src/amoeba_demo/launch/turtle_demo.launch b/documentation/ros_demo/catkin_ws/src/amoeba_demo/launch/turtle_demo.launch
new file mode 100644
index 0000000000000000000000000000000000000000..269cc9c68010991b2dabf7ec4c60820a2de1955f
--- /dev/null
+++ b/documentation/ros_demo/catkin_ws/src/amoeba_demo/launch/turtle_demo.launch
@@ -0,0 +1,9 @@
+<launch>
+
+ <include file="$(find rosbridge_server)/launch/rosbridge_websocket.launch" />
+
+ <node pkg="turtlesim" name="turtle" type="turtlesim_node"/>
+
+ <node pkg="amoeba_demo" name="controller" type="demo.py" />
+
+</launch>
diff --git a/documentation/ros_demo/catkin_ws/src/amoeba_demo/msg/Amoeba_msg.msg b/documentation/ros_demo/catkin_ws/src/amoeba_demo/msg/Amoeba_msg.msg
new file mode 100755
index 0000000000000000000000000000000000000000..6b7b3b5ebf111c7ec4951fd3cd99cb65f7b5a5fa
--- /dev/null
+++ b/documentation/ros_demo/catkin_ws/src/amoeba_demo/msg/Amoeba_msg.msg
@@ -0,0 +1,7 @@
+float64 px
+float64 py
+float64 theta
+float64 oracle
+float64 prev_lin
+float64 prev_ang
+bool learn
diff --git a/documentation/ros_demo/catkin_ws/src/amoeba_demo/package.xml b/documentation/ros_demo/catkin_ws/src/amoeba_demo/package.xml
new file mode 100644
index 0000000000000000000000000000000000000000..11daaf3f53e779739aae44f012224bd6dfcf784e
--- /dev/null
+++ b/documentation/ros_demo/catkin_ws/src/amoeba_demo/package.xml
@@ -0,0 +1,67 @@
+<?xml version="1.0"?>
+<package format="2">
+ <name>amoeba_demo</name>
+ <version>1.0.0</version>
+ <description>Demo for AMOEBA with ROS</description>
+
+ <maintainer email="hugo.roussel@univ-tlse3.fr">Hugo Roussel</maintainer>
+
+
+ <!-- One license tag required, multiple allowed, one license per tag -->
+ <!-- Commonly used license strings: -->
+ <!-- BSD, MIT, Boost Software License, GPLv2, GPLv3, LGPLv2.1, LGPLv3 -->
+ <license>BSD</license>
+
+
+ <!-- Url tags are optional, but multiple are allowed, one per tag -->
+ <!-- Optional attribute type can be: website, bugtracker, or repository -->
+ <!-- Example: -->
+ <!-- <url type="website">http://wiki.ros.org/amoeba_demo</url> -->
+
+
+ <!-- Author tags are optional, multiple are allowed, one per tag -->
+ <!-- Authors do not have to be maintainers, but could be -->
+ <!-- Example: -->
+ <!-- <author email="jane.doe@example.com">Jane Doe</author> -->
+
+
+ <!-- The *depend tags are used to specify dependencies -->
+ <!-- Dependencies can be catkin packages or system dependencies -->
+ <!-- Examples: -->
+ <!-- Use depend as a shortcut for packages that are both build and exec dependencies -->
+ <!-- <depend>roscpp</depend> -->
+ <!-- Note that this is equivalent to the following: -->
+ <!-- <build_depend>roscpp</build_depend> -->
+ <!-- <exec_depend>roscpp</exec_depend> -->
+ <!-- Use build_depend for packages you need at compile time: -->
+ <!-- <build_depend>message_generation</build_depend> -->
+ <!-- Use build_export_depend for packages you need in order to build against this package: -->
+ <!-- <build_export_depend>message_generation</build_export_depend> -->
+ <!-- Use buildtool_depend for build tool packages: -->
+ <!-- <buildtool_depend>catkin</buildtool_depend> -->
+ <!-- Use exec_depend for packages you need at runtime: -->
+ <!-- <exec_depend>message_runtime</exec_depend> -->
+ <!-- Use test_depend for packages you need only for testing: -->
+ <!-- <test_depend>gtest</test_depend> -->
+ <!-- Use doc_depend for packages you need only for building documentation: -->
+ <!-- <doc_depend>doxygen</doc_depend> -->
+ <buildtool_depend>catkin</buildtool_depend>
+ <build_depend>roscpp</build_depend>
+ <build_depend>rospy</build_depend>
+ <build_depend>std_msgs</build_depend>
+ <build_export_depend>roscpp</build_export_depend>
+ <build_export_depend>rospy</build_export_depend>
+ <build_export_depend>std_msgs</build_export_depend>
+ <exec_depend>roscpp</exec_depend>
+ <exec_depend>rospy</exec_depend>
+ <exec_depend>std_msgs</exec_depend>
+ <build_depend>message_generation</build_depend>
+ <exec_depend>message_runtime</exec_depend>
+
+
+ <!-- The export tag contains other, unspecified, tags -->
+ <export>
+ <!-- Other tools can request additional information be placed here -->
+
+ </export>
+</package>
diff --git a/documentation/ros_demo/catkin_ws/src/amoeba_demo/src/script/demo.py b/documentation/ros_demo/catkin_ws/src/amoeba_demo/src/script/demo.py
new file mode 100755
index 0000000000000000000000000000000000000000..4c64e53515311386d74f5d30e704091722442662
--- /dev/null
+++ b/documentation/ros_demo/catkin_ws/src/amoeba_demo/src/script/demo.py
@@ -0,0 +1,138 @@
+#!/usr/bin/python
+
+import time
+import rospy
+from std_srvs.srv import Empty
+from geometry_msgs.msg import Twist
+from amoeba_demo.msg import Amoeba_msg
+from turtlesim.msg import Pose
+
+learn = True
+tx = 0
+ty = 0
+theta = 0
+
+lin_vel = 0
+ang_vel = 0
+
+prev_lin_vel = 0
+prev_ang_vel = 0
+
+
+def control():
+ global learn
+ time.sleep(3)
+ rospy.loginfo("Learning ...")
+ for i in range(3):
+ rate.sleep()
+ forward(1)
+ rotate(1)
+ forward(1)
+ rotate(1)
+ forward(3)
+ rotate(1)
+ forward(1)
+ rotate(1)
+ forward(1)
+ rotate(1)
+ forward(3)
+ rotate(1)
+ learn = False
+ rospy.loginfo("replaying ...")
+ rospy.set_param('background_r', 150)
+ rospy.wait_for_service('clear')
+ clear_bg = rospy.ServiceProxy('clear', Empty)
+ clear_bg()
+ while not rospy.is_shutdown():
+ askAmoeba()
+
+def forward(value):
+ vel_msg = Twist()
+ vel_msg.linear.x = value
+ vel_msg.linear.y = 0
+ vel_msg.linear.z = 0
+ vel_msg.angular.x = 0
+ vel_msg.angular.y = 0
+ vel_msg.angular.z = 0
+ prev_lin_vel = value
+ prev_ang_vel = 0
+ pubTurtle.publish(vel_msg)
+ if learn :
+ pub(pubAmoebaLin, vel_msg.linear.x)
+ rate.sleep()
+
+def rotate(value):
+ vel_msg = Twist()
+ vel_msg.linear.x = 0
+ vel_msg.linear.y = 0
+ vel_msg.linear.z = 0
+ vel_msg.angular.x = 0
+ vel_msg.angular.y = 0
+ vel_msg.angular.z = value
+ prev_lin_vel = 0
+ prev_ang_vel = value
+ pubTurtle.publish(vel_msg)
+ if learn :
+ pub(pubAmoebaRot, vel_msg.angular.z)
+ rate.sleep()
+
+def askAmoeba():
+ global lin_vel, ang_vel, prev_lin_vel, prev_ang_vel
+ lin_vel = 0
+ ang_vel = 0
+ pub(pubAmoebaLin, 0)
+ pub(pubAmoebaRot, 0)
+ rate.sleep()
+ vel_msg = Twist()
+ vel_msg.linear.x = lin_vel
+ vel_msg.linear.y = 0
+ vel_msg.linear.z = 0
+ vel_msg.angular.x = 0
+ vel_msg.angular.y = 0
+ vel_msg.angular.z = ang_vel
+ prev_lin_vel = lin_vel
+ prev_ang_vel = ang_vel
+ pubTurtle.publish(vel_msg)
+ rate.sleep()
+
+def pub(publisher, oracle):
+ msg = Amoeba_msg()
+ msg.learn = learn
+ msg.px = tx
+ msg.py = ty
+ msg.theta = theta
+ msg.prev_lin = prev_lin_vel
+ msg.prev_ang = prev_ang_vel
+ msg.oracle = oracle
+ publisher.publish(msg)
+
+def callback(data):
+ global tx, ty, theta
+ tx = data.x * 10
+ ty = data.y * 10
+ theta = data.theta * 10
+
+def callbackLin(data):
+ global lin_vel
+ lin_vel = data.oracle
+
+
+def callbackRot(data):
+ global ang_vel
+ ang_vel = data.oracle
+
+
+if __name__ == '__main__':
+ print("Start control ...")
+ try:
+ rospy.init_node('control', anonymous=True)
+ pubTurtle = rospy.Publisher('turtle1/cmd_vel', Twist, queue_size=10)
+ pubAmoebaLin = rospy.Publisher('amoeba_lin', Amoeba_msg, queue_size=10)
+ pubAmoebaRot = rospy.Publisher('amoeba_rot', Amoeba_msg, queue_size=10)
+ rospy.Subscriber("turtle1/pose", Pose, callback)
+ rospy.Subscriber("amoeba_lin_res", Amoeba_msg, callbackLin)
+ rospy.Subscriber("amoeba_rot_res", Amoeba_msg, callbackRot)
+ rate = rospy.Rate(1) # 1hz
+ control()
+ except rospy.ROSInterruptException:
+ pass
diff --git a/documentation/ros_demo/clean.sh b/documentation/ros_demo/clean.sh
new file mode 100755
index 0000000000000000000000000000000000000000..25c18588815ada65f9fa88e4fb3351568d9c4998
--- /dev/null
+++ b/documentation/ros_demo/clean.sh
@@ -0,0 +1,8 @@
+#!/bin/sh
+
+rm amoeba.jar
+rm ./*.log
+rm -R ./saves/
+rm -R ./catkin_ws/build/
+rm -R ./catkin_ws/devel/
+rm -R ./catkin_ws/install/
diff --git a/documentation/ros_demo/setup.sh b/documentation/ros_demo/setup.sh
new file mode 100755
index 0000000000000000000000000000000000000000..1b5b7dd795eeb1bed2059d5a233a97bfc2afc8e8
--- /dev/null
+++ b/documentation/ros_demo/setup.sh
@@ -0,0 +1,5 @@
+#!/bin/sh
+
+(cd ../.. && mvn clean compile assembly:single -Dmain.class=ros.Main && cp AMOEBAonAMAK/target/AMOEBAonAMAK-1.0-jar-with-dependencies.jar documentation/ros_demo/amoeba.jar)
+(cd catkin_ws/ && catkin_make)
+echo "Done. If there's no error, you can do ./start.sh"
diff --git a/documentation/ros_demo/start.sh b/documentation/ros_demo/start.sh
new file mode 100755
index 0000000000000000000000000000000000000000..47b64389d1473a8874e07b267ef4db7982981f7a
--- /dev/null
+++ b/documentation/ros_demo/start.sh
@@ -0,0 +1,5 @@
+#!/bin/sh
+
+. ./catkin_ws/devel/setup.sh
+roslaunch amoeba_demo turtle_demo.launch &
+ ./start_amoebas.sh &
diff --git a/documentation/ros_demo/start_amoebas.sh b/documentation/ros_demo/start_amoebas.sh
new file mode 100755
index 0000000000000000000000000000000000000000..3f0316c9820aff7e05f5944be17320e624277dcb
--- /dev/null
+++ b/documentation/ros_demo/start_amoebas.sh
@@ -0,0 +1,5 @@
+#!/bin/sh
+
+java -jar amoeba.jar ws://localhost:9090 Amoeba_ros_demo.xml /amoeba_lin /amoeba_lin_res amoeba_demo/Amoeba_msg &
+java -jar amoeba.jar ws://localhost:9090 Amoeba_ros_demo.xml /amoeba_rot /amoeba_rot_res amoeba_demo/Amoeba_msg &
+
diff --git a/documentation/ros_demo/stop.sh b/documentation/ros_demo/stop.sh
new file mode 100755
index 0000000000000000000000000000000000000000..acbecfe70f37d0304867bde3e4a2ecb866073f42
--- /dev/null
+++ b/documentation/ros_demo/stop.sh
@@ -0,0 +1,13 @@
+#!/bin/sh
+
+for p in $(ps -A | grep ros | awk '{print $1;}')
+do
+ kill -15 $p
+done
+
+sleep 2
+
+for p in $(ps a | grep ros | awk '{print $1;}')
+do
+ kill -15 $p
+done
diff --git a/documentation/rosbridge.md b/documentation/rosbridge.md
new file mode 100644
index 0000000000000000000000000000000000000000..c9417fe256c5a405a130658d9065e9469103c0f8
--- /dev/null
+++ b/documentation/rosbridge.md
@@ -0,0 +1,45 @@
+# AMOEBA with ROS
+AMOEBAonAMAK come with utilities to allow it to communicate with ROS using [rosbridge](http://wiki.ros.org/rosbridge_suite). Rosbridge allow for simpler integration of existing java application into ROS, and is up-to-date (wich is not the case of rosjava).
+
+For anything ros-related, look at the `ros` package in `AMOEBAonAMAK`.
+
+Make sure you've read [How to use AMOEBA](usage.md).
+
+# Preparation
+You should have a `.msg` and `.xml` files. Make sure they have the same name (except for the extension).
+
+The .msg is a [ROS Message Type](http://wiki.ros.org/msg), setup your ROS project [to use it](http://wiki.ros.org/ROS/Tutorials/CreatingMsgAndSrv).
+
+Add [rosbridge](http://wiki.ros.org/rosbridge_suite) to your project.
+
+# Compile AMOEBA
+Do
+```
+mvn clean compile assembly:single -Dmain.class=ros.Main
+```
+You'll find the jar in AMOEBAonAMAK/target
+
+# Run
+Launch your project, including rosbridge-server.
+
+Launch `AMOEBAonAMAK/ros.Main` with the arguments `RosbridgeWebsocketURI ConfigFilePath RosToAmoebaTopic AmoebaToRosTopic MsgType`. In our example, and using the provided jar for Amoeba, the command is :
+```
+java -jar amoeba-ros.jar ws://localhost:9090 MyAmoebaConfig.xml /amoeba_request /amoeba_result your_ros_package/MyAmoebaMessageType
+```
+# Demo
+A demo is provided, you'll find it in `documentation/ros_demo`:
+Scripts are provided, for ease of use.
+- `setup.sh` compile amoeba and the catkin workspace.
+- `start.sh` launch the demo.
+- `stop.sh` stop ROS process created by the demo.
+- `clean.sh` remove files created by the above scripts.
+
+The demo is a turtlesim doing ovals. First we teach (blue background), then we ask amoeba to move the turtle (rose background). Keep in mind that the goal of the demo is to show exemple of ros integration with amoeba. It's not a demonstration of amoeba capabilities, so if the turtle does not learn, it's not a big problem.
+
+You can check that something is learned by looking at amoeba's window.
+
+The python node is at `documentation/ros_demo/catkin_ws/src/amoeba_demo/src/script/demo.py`
+
+In this demo, there's 2 amoebas (one for linear velocity, one for angular velocity), connected to ROS via rosbridge, and communicating with our python node via the topics `/amoeba_lin`, `/amoeba_lin_res`, `/amoeba_rot`, `/amoeba_rot_res`.
+
+ `/amoeba_lin` and `/amoeba_rot` are where we publish our request to the amoebas, and `/amoeba_lin_res` and `/amoeba_rot_res` is where we retrieve the result.
diff --git a/documentation/save_system.md b/documentation/save_system.md
new file mode 100644
index 0000000000000000000000000000000000000000..4219c489f00ceb30e162ed33cdf81f37300279d7
--- /dev/null
+++ b/documentation/save_system.md
@@ -0,0 +1,54 @@
+#The Save System
+The save system is composed of two main elements, and some GUI elements :
+
+## The Backup System :
+Found in `kernel.backup`.
+
+A backup system is an object responsible for reading/writing the state of amoeba from/to a file. It implement the interface `IBackupSystem`. The implementation provided is `BackupSystem` and use xml to store data.
+
+Usage :
+```Java
+AMOEBA amoeba = new AMOEBA()
+IBackupSystem backupSystem = new BackupSystem(amoeba);
+backupSystem.load(new File("path/to/a/save.xml"));
+// do some learning with the amoeba ...
+backupSystem.save(new File("path/to/a/new/file.xml"))
+```
+
+## The Save Helper :
+Found in `kernel.backup`.
+
+A save helper is an object that provide additional functionality over a BackupSystem for the user or other components. Most importantly it :
+- Create a temporary directory for saves
+- Allow automatic saving during amoeba execution
+- Add the options to save/load on the GUI
+- Add functionality used by the SaveExplorer.
+
+See `ISaveHelper` for more.
+
+Two implementation are provided : the fully functioning `SaveHelperImpl` and `SaveHelperDummy` that do nothing. The dummy is used to deactivate ALL automatic saving, giving a HUGE performance boost.
+
+Each amoeba has a save helper, available with `amoeba.saver`
+```Java
+AMOEBA amoeba = new AMOEBA();
+// This constructor initialize the amoeba's saver with a dummy, meaning :
+amoeba.saver.save("this_does_not_save");
+// will do nothing
+
+// or ...
+AMOEBA amoeba = new AMOEBA("path/to/save.xml", null);
+// This constructor create and use a SaveHelperImpl to initilize the amoeba
+amoeba.saver.save("a/valid/path/save.xml");
+// will create a save, and
+amoeba.saver.autosave();
+// will create a save in the temporary directory creates by the save helper, located in
+System.out.println(SaveHelperImpl.dir)
+```
+If amoeba crash, the save files will not be automatically deleted, you may have to manually clean the save directory.
+
+## The Save Explorer
+Found in `gui.saveExplorer`.
+
+The save explorer read saves from an amoeba's SaveHelper and offer some graphical tool, most importantly the ability to preview a save and quickly cycle trough saves. Allowing to visually play back the execution of an amoeba.
+
+See the [GUI description](gui.md) for more detail on the GUI.
diff --git a/documentation/usage.md b/documentation/usage.md
index b96a4288d1f01f4723cad49bde49d98b163be9a9..b7235148d0d75d1ce59ae9429eb6fd0dcb84c012 100644
--- a/documentation/usage.md
+++ b/documentation/usage.md
@@ -15,7 +15,8 @@ Depending on your problem, determine what AMOEBA should learn, and from what. Bu
## Create a config file
A config file is a xml file used to initialize your amoeba. Most importantly it contain the list of percepts.
-Your config file should look like this :
+You can use `utils/genFiles.py` to generate your xml file based on a list of percept. `python genFiles.py MySystem false px py` will create `MySystem.xml` (and `MySystem.msg`, but ignore it if you don't use [AMOEBA and ROS](rosbridge.md)) containing something looking like the following example :
+(if you don't want to use python, a java class doing the same job is available at `utils.XmlConfigGenerator`)
```xml
<?xml version="1.0" encoding="UTF-8"?>
<System>
@@ -32,7 +33,6 @@ Your config file should look like this :
<Controller Name="Controller">
<ErrorMargin ErrorAllowed="2000.0" AugmentationFactorError="5.0" DiminutionFactorError="0.4" MinErrorAllowed="0.1" NConflictBeforeAugmentation="40" NSuccessBeforeDiminution="80" />
- <InexactMargin InexactAllowed="500.0" AugmentationInexactError="2.5" DiminutionInexactError="0.2" MinInexactAllowed="0.05" NConflictBeforeInexactAugmentation="40" NSuccessBeforeInexactDiminution="80" />
</Controller>
</StartingAgents>
@@ -43,6 +43,8 @@ With :
- **Sensor** represent one percept, make sure to remember the name, we will use it later. `Enum` tell AMOEBA whether or not the variable linked to this percept is continuous, or discrete.
- **Controller** these are hyperparameter for the AMOEBA, they affect how fast and how well an amoeba learn. They can be dynamically adjusted during training, AMOEBA even does it automatically ! You still might want to adjust `MinErrorAllowed` and `MinInexactAllowed`, as they're dependent on your problem.
+If you want to use AMOEBA with ROS, continue [here](rosbridge.md).
+
## Create your studied system java class
We have to tell AMOEBA what we want it to learn. Although we can hand-feed an amoeba with our data, providing a studied system allow to make full use of the graphical user interface.
@@ -142,6 +144,6 @@ public static void main(String[] args) {
}
}
```
-We can ask amoeba how well it performed on the last prediction with `amoeba.getHeads().get(0).getCriticity()`.
+We can ask amoeba how well it performed on the last prediction with `amoeba.getHeadAgent().getCriticity()`.
For more example on how to use amoeba, check `AdvancedMain.java`, `MinimalMain.java`, and `Main.java` in the `experiments` package.
\ No newline at end of file
diff --git a/pom.xml b/pom.xml
index ff2606e5a3236ffb1eb31133c1c82de75692692c..ce38471ffd90a9284043a296ffae4b4e60c0a94e 100644
--- a/pom.xml
+++ b/pom.xml
@@ -27,6 +27,12 @@
<resource>
<directory>resources</directory>
</resource>
+ <resource>
+ <directory>src</directory>
+ <includes>
+ <include>**/*.fxml</include>
+ </includes>
+ </resource>
</resources>
<pluginManagement>
<plugins>
@@ -35,12 +41,14 @@
<artifactId>maven-compiler-plugin</artifactId>
<version>3.8.0</version>
<configuration>
- <release>8</release>
+ <source>1.8</source>
+ <target>1.8</target>
</configuration>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-surefire-plugin</artifactId>
+ <version>2.22.2</version>
<configuration>
<reuseForks>false</reuseForks>
<forkCount>1C</forkCount>
@@ -75,10 +83,9 @@
<dependencies>
<dependency>
- <groupId>junit</groupId>
- <artifactId>junit</artifactId>
- <version>4.8.2</version>
- <scope>test</scope>
+ <groupId>org.junit.jupiter</groupId>
+ <artifactId>junit-jupiter-engine</artifactId>
+ <version>5.4.2</version>
</dependency>
<dependency>
<groupId>org.openjfx</groupId>
diff --git a/utils/genFiles.py b/utils/genFiles.py
new file mode 100644
index 0000000000000000000000000000000000000000..25a5ee7d4de202abd6faa2e8cdbb17bedb8dbc6a
--- /dev/null
+++ b/utils/genFiles.py
@@ -0,0 +1,42 @@
+import sys
+import os
+
+if (len(sys.argv) < 4) :
+ print("Usage : %s outFileName isEnum percept1 [percept2 ...]")
+ print("Generate a .msg for ROS and a .xml for AMOEBA based on the percepts names provided.")
+ exit(0)
+
+fileName = sys.argv[1][0].upper()+sys.argv[1][1:]
+
+with open(fileName+".msg", "w") as msgFile:
+ for percept in sys.argv[3:] :
+ msgFile.write("float64 %s\n" % percept)
+ msgFile.write("float64 oracle\n")
+ msgFile.write("bool learn")
+
+with open(fileName+".xml", "w") as xmlFile:
+ start = """
+<?xml version="1.0" encoding="UTF-8"?>
+<System>
+
+ <Configuration>
+ <Learning allowed = "true" creationOfNewContext = "true" loadPresetContext = "false"></Learning>
+ </Configuration>
+
+ <StartingAgents>
+"""
+ xmlFile.write(start)
+ for percept in sys.argv[3:] :
+ xmlFile.write("\t\t<Sensor Name=\"%s\" Enum=\"%s\" />\n" % (percept, sys.argv[2]))
+ end = """
+ <Controller Name="Controller">
+ <ErrorMargin ErrorAllowed="2000.0" AugmentationFactorError="5.0" DiminutionFactorError="0.4" MinErrorAllowed="0.1" NConflictBeforeAugmentation="40" NSuccessBeforeDiminution="80" />
+
+ </Controller>
+ </StartingAgents>
+
+</System>
+"""
+ xmlFile.write(end)
+
+exit(0)