From c4985f2ed525341a2408ecdb34a5808a5c549101 Mon Sep 17 00:00:00 2001
From: Hugo Roussel <hugo.roussel@univ-tlse3.fr>
Date: Thu, 11 Jul 2019 16:16:58 +0200
Subject: [PATCH] Refactor LocalModel
---
AMOEBAonAMAK/src/agents/context/Context.java | 36 ++----
.../agents/context/localModel/LocalModel.java | 121 +++++++++++++-----
.../LocalModelMillerRegression.java | 114 +++++------------
AMOEBAonAMAK/src/agents/head/Head.java | 13 +-
AMOEBAonAMAK/src/kernel/AMOEBA.java | 2 +-
5 files changed, 138 insertions(+), 148 deletions(-)
diff --git a/AMOEBAonAMAK/src/agents/context/Context.java b/AMOEBAonAMAK/src/agents/context/Context.java
index 0f601e60..652269f8 100644
--- a/AMOEBAonAMAK/src/agents/context/Context.java
+++ b/AMOEBAonAMAK/src/agents/context/Context.java
@@ -150,8 +150,7 @@ public class Context extends AmoebaAgent {
// world.trace(new ArrayList<String>(Arrays.asList(this.getName(),"NEW EXP",
// firstPoint.toString())));
- localModel.updateModel(this.getCurrentExperiment(), getAmas().data.learningSpeed,
- getAmas().data.numberOfPointsForRegression);
+ localModel.updateModel(this.getCurrentExperiment(), getAmas().data.learningSpeed);
getAmas().addAlteredContext(this);
this.setName(String.valueOf(this.hashCode()));
@@ -212,7 +211,7 @@ public class Context extends AmoebaAgent {
Double[] coef = ((LocalModelMillerRegression) fatherContext.localModel).getCoef();
((LocalModelMillerRegression) this.localModel).setCoef(coef);
this.actionProposition = ((LocalModelMillerRegression) fatherContext.localModel)
- .getProposition(fatherContext);
+ .getProposition();
}
getAmas().addAlteredContext(this);
@@ -274,13 +273,12 @@ public class Context extends AmoebaAgent {
Double[] coef = ((LocalModelMillerRegression) bestNearestContext.localModel).getCoef();
((LocalModelMillerRegression) this.localModel).setCoef(coef);
this.actionProposition = ((LocalModelMillerRegression) bestNearestContext.localModel)
- .getProposition(bestNearestContext);
+ .getProposition();
}
localModel.setFirstExperiments(new ArrayList<Experiment>(bestNearestContext.getLocalModel().getFirstExperiments()));
- localModel.updateModel(this.getCurrentExperiment(), getAmas().data.learningSpeed,
- getAmas().data.numberOfPointsForRegression);
+ localModel.updateModel(this.getCurrentExperiment(), getAmas().data.learningSpeed);
getAmas().addAlteredContext(this);
this.setName(String.valueOf(this.hashCode()));
@@ -543,7 +541,7 @@ public class Context extends AmoebaAgent {
((LocalModelMillerRegression) this.localModel).setCoef(coef);
this.actionProposition = ((LocalModelMillerRegression) betterContext.getLocalModel())
- .getProposition(betterContext);
+ .getProposition();
}
public void analyzeResults3(Head head, Context closestContextToOracle) {
@@ -959,14 +957,6 @@ public class Context extends AmoebaAgent {
return exp;
}
- private boolean tryNewExperiment2() {
- if (localModel.distance(getCurrentExperiment()) < 10.0) {
- localModel.updateModelWithExperimentAndWeight(getCurrentExperiment(), 0.5, 100);
- return true;
- }
- return false;
- }
-
public double sumOfRangesLengths() {
double sum = 0;
@@ -1910,8 +1900,8 @@ public class Context extends AmoebaAgent {
s += "Context : " + getName() + "\n";
s += "Model : ";
s += this.localModel.getCoefsFormula() + "\n";
- s += "Max Prediction " + getLocalModel().getMaxProposition(this) + "\n";
- s += "Min Prediction " + getLocalModel().getMinProposition(this) + "\n";
+ s += "Max Prediction " + getLocalModel().getMaxProposition() + "\n";
+ s += "Min Prediction " + getLocalModel().getMinProposition() + "\n";
return s;
}
@@ -1922,8 +1912,8 @@ public class Context extends AmoebaAgent {
for(int i =1;i<localModel.getCoef().length;i++) {
array.add(""+localModel.getCoef()[i]);
}
- array.add(""+ getLocalModel().getMinProposition(this));
- array.add(""+ getLocalModel().getMaxProposition(this));
+ array.add(""+ getLocalModel().getMinProposition());
+ array.add(""+ getLocalModel().getMaxProposition());
return array;
}
@@ -1951,8 +1941,8 @@ public class Context extends AmoebaAgent {
s += "Mean Distance To Regression " + criticalities.getCriticalityMean("distanceToRegression") + "\n";
s += "Distance To Regression Allowed " + regressionPerformance.getPerformanceIndicator() +"\n\n";
- s += "Max Prediction " + getLocalModel().getMaxProposition(this) + "\n";
- s += "Min Prediction " + getLocalModel().getMinProposition(this) + "\n\n";
+ s += "Max Prediction " + getLocalModel().getMaxProposition() + "\n";
+ s += "Min Prediction " + getLocalModel().getMinProposition() + "\n\n";
s += "ASKED REQUEST " + waitingRequests.size() + "\n";
for(EndogenousRequest rqt : waitingRequests) {
@@ -2076,7 +2066,7 @@ public class Context extends AmoebaAgent {
}
public double getActionProposal() {
- return localModel.getProposition(this);
+ return localModel.getProposition();
}
public double getCenterByPercept(Percept pct) {
@@ -2133,7 +2123,7 @@ public class Context extends AmoebaAgent {
*/
public void setLocalModel(LocalModel localModel) {
this.localModel = localModel;
- this.localModel.context = this;
+ this.localModel.setContext(this);
}
diff --git a/AMOEBAonAMAK/src/agents/context/localModel/LocalModel.java b/AMOEBAonAMAK/src/agents/context/localModel/LocalModel.java
index bb2bec7d..91d1f1da 100644
--- a/AMOEBAonAMAK/src/agents/context/localModel/LocalModel.java
+++ b/AMOEBAonAMAK/src/agents/context/localModel/LocalModel.java
@@ -5,53 +5,106 @@ import java.util.HashMap;
import agents.context.Context;
import agents.context.Experiment;
-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.
+ * A LocalModel is used by a Context to store information and generate prediction.
*/
-public abstract class LocalModel {
-
- public Context context;
+public interface LocalModel {
/**
- * Instantiates a new local model agent.
+ * Sets the context that use the LocalModel
+ * @param context
*/
- public LocalModel(Context associatedContext) {
- context = associatedContext;
- }
-
+ public void setContext(Context context);
+
+ /**
+ * gets the context that use the LocalModel
+ * @return
+ */
+ public Context getContext();
+
/**
* Gets the proposition.
*
- * @param context the context
* @return the proposition
*/
- public abstract double getProposition(Context context);
- public abstract double getProposition(Experiment experiment);
- public abstract double getMaxProposition(Context context);
- public abstract HashMap<String, Double> getMax(Context context);
- public abstract double getMinProposition(Context context);
+ 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
+ * @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> getMax();
- public abstract double getProposition(ArrayList<Experiment> experimentsList, Experiment experiment);
+ /**
+ * Gets the proposition with the lowest value possible
+ * @return
+ */
+ public double getMinProposition();
- public abstract String getCoefsFormula();
-
- public abstract void updateModelWithExperiments(ArrayList<Experiment> experimentsList);
- public abstract void updateModelWithExperimentAndWeight(Experiment newExperiment, double weight, int numberOfPointsForRegression);
- public abstract void updateModel(Experiment newExperiment, double weight, int numberOfPointsForRegression);
- public abstract String coefsToString();
- public abstract double distance(Experiment experiment);
- public abstract ArrayList<Experiment> getFirstExperiments();
- public abstract void setFirstExperiments( ArrayList<Experiment> frstExp);
- public abstract boolean finishedFirstExperiments();
-
- public abstract Double[] getCoef();
- public abstract void setCoef(Double[] coef);
+ /**
+ * 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);
- public abstract TypeLocalModel getType();
+ /**
+ * Gets the {@link TypeLocalModel} corresponding to this LocalModel
+ */
+ public TypeLocalModel getType();
}
diff --git a/AMOEBAonAMAK/src/agents/context/localModel/LocalModelMillerRegression.java b/AMOEBAonAMAK/src/agents/context/localModel/LocalModelMillerRegression.java
index a27ec497..24c73fc0 100644
--- a/AMOEBAonAMAK/src/agents/context/localModel/LocalModelMillerRegression.java
+++ b/AMOEBAonAMAK/src/agents/context/localModel/LocalModelMillerRegression.java
@@ -15,7 +15,9 @@ import utils.TRACE_LEVEL;
/**
* The Class LocalModelMillerRegression.
*/
-public class LocalModelMillerRegression extends LocalModel{
+public class LocalModelMillerRegression implements LocalModel{
+
+ private Context context;
/** The n parameters. */
private int nParameters;
@@ -35,7 +37,7 @@ public class LocalModelMillerRegression extends LocalModel{
* @param world the world
*/
public LocalModelMillerRegression(Context associatedContext) {
- super(associatedContext);
+ context = associatedContext;
ArrayList<Percept> var = associatedContext.getAmas().getPercepts();
this.nParameters = var.size();
regression = new Regression(nParameters,true);
@@ -43,7 +45,7 @@ public class LocalModelMillerRegression extends LocalModel{
}
public LocalModelMillerRegression(Context associatedContext, Double[] coefsCopy, List<Experiment> fstExperiments) {
- super(associatedContext);
+ context = associatedContext;
ArrayList<Percept> var = associatedContext.getAmas().getPercepts();
this.nParameters = var.size();
regression = new Regression(nParameters,true);
@@ -51,6 +53,16 @@ public class LocalModelMillerRegression extends LocalModel{
firstExperiments = new ArrayList<Experiment>(fstExperiments);
}
+ @Override
+ public void setContext(Context context) {
+ this.context = context;
+ }
+
+ @Override
+ public Context getContext() {
+ return context;
+ }
+
/**
* Sets the coef.
*
@@ -71,7 +83,8 @@ public class LocalModelMillerRegression extends LocalModel{
return coefs;
}
- public double getProposition(Context context) {
+ @Override
+ public double getProposition() {
ArrayList<Percept> percepts = context.getAmas().getPercepts();
@@ -93,11 +106,8 @@ public class LocalModelMillerRegression extends LocalModel{
- public double getProposition(Context context, double[] situation) {
-
- ArrayList<Percept> percepts = context.getAmas().getPercepts();
+ private double getProposition(Context context, double[] situation) {
-
double result = coefs[0];
if (coefs[0] == Double.NaN) System.exit(0);
@@ -112,7 +122,8 @@ public class LocalModelMillerRegression extends LocalModel{
return result;
}
- public double getMaxProposition(Context context) {
+ @Override
+ public double getMaxProposition() {
ArrayList<Percept> percepts = context.getAmas().getPercepts();
double result = coefs[0];
@@ -133,7 +144,8 @@ public class LocalModelMillerRegression extends LocalModel{
return result;
}
- public HashMap<String, Double> getMax(Context context){
+ @Override
+ public HashMap<String, Double> getMax(){
ArrayList<Percept> percepts = context.getAmas().getPercepts();
HashMap<String, Double> result = new HashMap<String, Double>();
@@ -162,7 +174,8 @@ public class LocalModelMillerRegression extends LocalModel{
return result;
}
- public double getMinProposition(Context context) {
+ @Override
+ public double getMinProposition() {
ArrayList<Percept> percepts = context.getAmas().getPercepts();
double result = coefs[0];
@@ -183,31 +196,6 @@ public class LocalModelMillerRegression extends LocalModel{
return result;
}
- public double getProposition(ArrayList<Experiment> experimentsList, Experiment experiment) {
-
-
-
- if (experimentsList.size() == 1) {
- return experimentsList.get(0).getOracleProposition();
- }
- else {
- 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] * experiment.getValuesAsArray()[i-1];
-
- }
-
- return result;
- }
-
-
- }
-
public double getProposition(Experiment experiment) {
if (coefs[0] == Double.NaN) System.exit(0);
@@ -224,6 +212,7 @@ public class LocalModelMillerRegression extends LocalModel{
}
+ @Override
public String getCoefsFormula() {
String result = "" +coefs[0];
// //System.out.println("Result 0" + " : " + result);
@@ -239,47 +228,8 @@ public class LocalModelMillerRegression extends LocalModel{
return result;
}
-
@Override
- public void updateModelWithExperiments(ArrayList<Experiment> experimentsList) {
-
- regression = new Regression(nParameters,true);
-
- for (Experiment exp : experimentsList) {
-
- regression.addObservation(exp.getValuesAsArray(), exp.getOracleProposition());
-
-
- }
-
-
-
- while (regression.getN() < experimentsList.get(0).getValuesAsLinkedHashMap().size() + 2) { //TODO : to improve
-
- regression.addObservation(experimentsList.get(0).getValuesAsArray(), experimentsList.get(0).getOracleProposition());
-
- System.out.println("Observations " + regression.getN());
-
- System.out.println(experimentsList.get(0).getValuesAsLinkedHashMap().toString());
- for (int i = 0 ; i < experimentsList.get(0).getValuesAsArray().length ; i++ ) {
- System.out.print(experimentsList.get(0).getValuesAsArray()[i] + " " );
- }
- System.out.println(experimentsList.get(0).getOracleProposition() + " " );
- }
-
-
-
- double[] coef = regression.regress().getParameterEstimates();
- coefs = new Double[coef.length];
- for(int i = 0; i < coef.length; i++) {
- coefs[i] = coef[i];
- }
-
-
- }
-
-
- public void updateModel(Experiment newExperiment, double weight, int numberOfPointsForRegression) {
+ 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)) {
@@ -287,7 +237,7 @@ public class LocalModelMillerRegression extends LocalModel{
updateModel();
}else {
- updateModelWithExperimentAndWeight(newExperiment, weight, numberOfPointsForRegression);
+ updateModelWithExperimentAndWeight(newExperiment, weight, context.getAmas().data.numberOfPointsForRegression);
}
context.getAmas().addSpatiallyAlteredContextForUnityUI(context);
@@ -490,12 +440,8 @@ public class LocalModelMillerRegression extends LocalModel{
return new Pair<double[][], double[]>(artificalExperiments, artificalResults);
}
-
-
-
-
-
+ @Override
public double distance(Experiment experiment) {
if (coefs[0] == Double.NaN) System.exit(0);
@@ -521,14 +467,17 @@ public class LocalModelMillerRegression extends LocalModel{
}
+ @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) {
@@ -539,6 +488,7 @@ public class LocalModelMillerRegression extends LocalModel{
return coefsString;
}
+ @Override
public boolean finishedFirstExperiments() {
return firstExperiments.size()>= (nParameters + 2);
}
diff --git a/AMOEBAonAMAK/src/agents/head/Head.java b/AMOEBAonAMAK/src/agents/head/Head.java
index c3070c57..390b1281 100644
--- a/AMOEBAonAMAK/src/agents/head/Head.java
+++ b/AMOEBAonAMAK/src/agents/head/Head.java
@@ -1111,15 +1111,13 @@ public class Head extends AmoebaAgent {
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.numberOfPointsForRegression);
+ 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,
- getAmas().data.numberOfPointsForRegression);
+ activatedContext.getLocalModel().updateModel(activatedContext.getCurrentExperiment(), getAmas().data.learningSpeed);
}
@@ -1181,7 +1179,7 @@ public class Head extends AmoebaAgent {
getEnvironment().trace(TRACE_LEVEL.DEBUG, new ArrayList<String>(Arrays.asList("MODEL DISTANCE",
activatedContexts.get(0).getName(), "" + distanceToOracleForActivatedContext)));
activatedContexts.get(0).getLocalModel().updateModel(activatedContexts.get(0).getCurrentExperiment(),
- getAmas().data.learningSpeed, getAmas().data.numberOfPointsForRegression);
+ getAmas().data.learningSpeed);
}
} else {
@@ -1189,7 +1187,7 @@ public class Head extends AmoebaAgent {
Arrays.asList("MODEL DISTANCE", activatedContexts.get(0).getName(), "" + activatedContexts.get(0)
.getLocalModel().distance(activatedContexts.get(0).getCurrentExperiment()))));
activatedContexts.get(0).getLocalModel().updateModel(activatedContexts.get(0).getCurrentExperiment(),
- getAmas().data.learningSpeed, getAmas().data.numberOfPointsForRegression);
+ getAmas().data.learningSpeed);
}
// world.trace(new ArrayList<String>(Arrays.asList("MODEL
@@ -1284,8 +1282,7 @@ public class Head extends AmoebaAgent {
}
- closestContextToOracle.getLocalModel().updateModel(closestContextToOracle.getCurrentExperiment(), getAmas().data.learningSpeed,
- getAmas().data.numberOfPointsForRegression);
+ closestContextToOracle.getLocalModel().updateModel(closestContextToOracle.getCurrentExperiment(), getAmas().data.learningSpeed);
activatedContextsCopyForUpdates = new ArrayList<Context>(activatedContexts);
for (Context activatedContext : activatedContexts) {
diff --git a/AMOEBAonAMAK/src/kernel/AMOEBA.java b/AMOEBAonAMAK/src/kernel/AMOEBA.java
index 4da9804e..ef405f38 100644
--- a/AMOEBAonAMAK/src/kernel/AMOEBA.java
+++ b/AMOEBAonAMAK/src/kernel/AMOEBA.java
@@ -431,7 +431,7 @@ public class AMOEBA extends Amas<World> implements IAMOEBA {
ArrayList<HashMap<String, Double>> sol = new ArrayList<>();
for(Context c : pac) {
- sol.add(c.getLocalModel().getMax(c));
+ sol.add(c.getLocalModel().getMax());
}
HashMap<String, Double> max = new HashMap<>();
--
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