ADD: first steps of endogenous exploitation

AMOEBA3/src/experiments/badContext/BadContextLauncherEasy.java

@@ -35,8 +35,8 @@ public class BadContextLauncherEasy implements Serializable {
 		
 		/* These method calls allow to setup AMOEBA*/
 		amoeba.setLocalModel(TypeLocalModel.MILLER_REGRESSION);
-		amoeba.setDataForErrorMargin(10, 0.01, 0.01, 10, 5, 5);
-		amoeba.setDataForInexactMargin(0.1, 0.01, 0.01, 0.1, 5, 5);
+		amoeba.setDataForErrorMargin(1, 0.01, 0.01, 1, 5, 5);
+		amoeba.setDataForInexactMargin(0.5, 0.01, 0.01, 0.5, 5, 5);
 		
 		/* Default */
 //		amoeba.setAVT_acceleration(2);

AMOEBA3/src/experiments/badContext/FILE.java

+package experiments.badContext;
+
+
+//Packages  importer afin d'utiliser l'objet File
+
+import java.io.FileNotFoundException;
+import java.io.PrintWriter;
+
+public class FILE {
+	
+	PrintWriter pw;
+
+	
+	public FILE(String path, String folder, String name){
+		    try {
+				pw = new PrintWriter(path + 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 write(Double f1, Double f2, Double f3, Double f4, Double f5){
+      	pw.println(f1.toString() + ";" + f2.toString() + ";" + f3.toString() + ";" + f4.toString() + ";" + f5.toString());
+	}
+	
+	public void write(String f1, String f2, String f3, String f4, String f5){
+      	pw.println(f1 + ";" + f2 + ";" + f3 + ";" + f4 + ";" + f5);
+	}
+	
+	public void write(String f1, String f2, String f3, String f4){
+      	pw.println(f1 + ";" + f2 + ";" + f3 + ";" + f4);
+	}
+	
+	public void write(String f1, String f2, String f3){
+      	pw.println(f1 + ";" + f2 + ";" + f3);
+	}
+	
+	public void write(String f1, String f2){
+      	pw.println(f1 + ";" + f2);
+	}
+	
+	public void close(){
+		pw.close();
+	}
+	
+public static void main(String[] args) {
+	
+  FILE test = new FILE("","19122017","test");
+
+  test.write(0.0000d, 0.0045d);
+  test.write(0.0000d, 0.0045d);
+
+  
+  
+  test.close();
+}
+  
+}

AMOEBA3/src/experiments/badContext/F_XY_ComparativeLauncher.java

+package experiments.badContext;
+
+import java.io.Serializable;
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.HashMap;
+import java.util.SimpleTimeZone;
+
+import mas.agents.Agent;
+import mas.agents.percept.ContextProjection;
+import mas.agents.percept.Percept;
+import mas.agents.context.Context;
+import mas.agents.localModel.TypeLocalModel;
+import mas.init.amoeba.AMOEBAFactory;
+import mas.kernel.AMOEBA;
+
+// TODO: Auto-generated Javadoc
+/**
+ * The Class BadContextLauncherEasy.
+ */
+public class F_XY_ComparativeLauncher implements Serializable {
+
+
+	public static final boolean viewer = false;
+	public static final boolean verboseriticity = true;
+
+	public static void main(String[] args) {
+		launch(viewer);
+	}
+
+	public static void launch(boolean viewer) {
+	
+		/*Here we create AMOEBA.*/
+		AMOEBA amoeba1 = AMOEBAFactory.createAMOEBA(viewer,"BadContext_solver.xml");
+		AMOEBA amoeba2 = AMOEBAFactory.createAMOEBA(true,"BadContext_solver.xml");
+		AMOEBA amoeba3 = AMOEBAFactory.createAMOEBA(true,"BadContext_solver.xml");
+		AMOEBA amoeba4 = AMOEBAFactory.createAMOEBA(viewer,"BadContext_solver.xml");
+		
+		FILE criticitiesFile = new FILE("C:/Users/dato/Documents/THESE/XP/","23102018", "Test_Errors_Cycles1000_FIX200_100_50_25NB40_80_80_160");
+		FILE agentsContextesFile = new FILE("C:/Users/dato/Documents/THESE/XP/","23102018", "Test_NB_CTXT_Cycles1000_FIX200_100_50_25NB40_80_80_160");
+		
+		
+		
+		
+		/* These method calls allow to setup AMOEBA*/
+		amoeba1.setLocalModel(TypeLocalModel.MILLER_REGRESSION);
+		amoeba2.setLocalModel(TypeLocalModel.MILLER_REGRESSION);
+		amoeba3.setLocalModel(TypeLocalModel.MILLER_REGRESSION);
+		amoeba4.setLocalModel(TypeLocalModel.MILLER_REGRESSION);
+		
+		//Errors margins
+		amoeba1.setDataForErrorMargin(200, 5, 0.4, 0.1, 50000, 10000);
+		amoeba1.setDataForInexactMargin(100.05, 2.5, 0.2, 0.05, 5000, 10000);
+		amoeba2.setDataForErrorMargin(50, 5, 0.4, 0.1, 10000, 20000);
+		amoeba2.setDataForInexactMargin(25, 2.5, 0.2, 0.05, 10000, 20000);
+		amoeba3.setDataForErrorMargin(0.1, 5, 0.4, 0.1, 40, 80);
+		amoeba3.setDataForInexactMargin(0.05, 2.5, 0.2, 0.05, 40, 80);
+		amoeba4.setDataForErrorMargin(0.1, 5, 0.4, 0.1, 80, 160);
+		amoeba4.setDataForInexactMargin(0.05, 2.5, 0.2, 0.05, 80, 160);
+		
+		
+		criticitiesFile.write("ErrorMargin(200, 5, 0.4, 0.1, 50000, 10000) InexactMargin(100.05, 2.5, 0.2, 0.05, 5000, 10000)",
+								"ErrorMargin(50, 5, 0.4, 0.1, 10000, 20000) InexactMargin(25, 2.5, 0.2, 0.05, 10000, 20000)", 
+								"ErrorMargin(0.1, 5, 0.4, 0.1, 40, 80) InexactMargin(0.05, 2.5, 0.2, 0.05, 40, 80)", 
+								"ErrorMargin(0.1, 5, 0.4, 0.1, 80, 160) InexactMargin(0.05, 2.5, 0.2, 0.05, 80, 160)");
+		agentsContextesFile.write("ErrorMargin(200, 5, 0.4, 0.1, 50000, 10000) InexactMargin(100.05, 2.5, 0.2, 0.05, 5000, 10000)",
+								"ErrorMargin(50, 5, 0.4, 0.1, 10000, 20000) InexactMargin(25, 2.5, 0.2, 0.05, 10000, 20000)", 
+								"ErrorMargin(0.1, 5, 0.4, 0.1, 40, 80) InexactMargin(0.05, 2.5, 0.2, 0.05, 40, 80)", 
+								"ErrorMargin(0.1, 5, 0.4, 0.1, 80, 160) InexactMargin(0.05, 2.5, 0.2, 0.05, 80, 160)");
+		
+		
+		amoeba1.setRememberState(false);
+		amoeba1.setGenerateCSV(false);
+		amoeba2.setRememberState(false);
+		amoeba2.setGenerateCSV(false);
+		amoeba3.setRememberState(false);
+		amoeba3.setGenerateCSV(false);
+		amoeba4.setRememberState(false);
+		amoeba4.setGenerateCSV(false);
+		
+		/* This is the initialization of the studied system. It's only for the sake of example, not a part of AMOEBA initialization*/
+		F_XY_Manager bcm = new F_XY_Manager(50.0);
+		
+
+		double averageCriticity1 = 0.0;
+		double averageCriticity2 = 0.0;
+		double averageCriticity3 = 0.0;
+		double averageCriticity4 = 0.0;
+		
+		
+		for (int i = 0 ; i < 100 ; i++) {
+
+			/* This is the studied system part. Feel free to use any data source.*/
+			bcm.playOneStep(0);
+			
+			/*This is a learning step of AMOEBA*/
+			amoeba1.learn(new HashMap<String, Double>(bcm.getOutput()));
+			averageCriticity1 = amoeba1.getAveragePredictionCriticity();
+			
+			amoeba2.learn(new HashMap<String, Double>(bcm.getOutput()));
+			averageCriticity2 = amoeba2.getAveragePredictionCriticity();
+			
+			amoeba3.learn(new HashMap<String, Double>(bcm.getOutput()));
+			averageCriticity3 = amoeba3.getAveragePredictionCriticity();
+			
+			amoeba4.learn(new HashMap<String, Double>(bcm.getOutput()));
+			averageCriticity4 = amoeba4.getAveragePredictionCriticity();
+			
+			criticitiesFile.write(averageCriticity1, averageCriticity2, averageCriticity3, averageCriticity4);
+			agentsContextesFile.write(amoeba1.getNumberOfContextAgents(), amoeba2.getNumberOfContextAgents(), amoeba3.getNumberOfContextAgents(), amoeba4.getNumberOfContextAgents());
+			
+			
+		}
+		
+		/*for (int i = 0 ; i < 1000 ; i++) {
+			bcm.playOneStep(0);
+			HashMap<String, Double> data = new HashMap<String, Double>(bcm.getOutput());
+		//	data.remove("test");
+			System.out.println("Test request : " + amoeba.request(data));
+		}*/
+		
+
+		
+		
+		
+		
+
+		criticitiesFile.close();
+		agentsContextesFile.close();
+		
+
+	}
+
+}

AMOEBA3/src/experiments/badContext/F_XY_Launcher.java

@@ -36,9 +36,19 @@ public class F_XY_Launcher implements Serializable {
 		/* These method calls allow to setup AMOEBA*/
 		amoeba.setLocalModel(TypeLocalModel.MILLER_REGRESSION);
 		
-		//Beau rsultat
-		amoeba.setDataForErrorMargin(0.1, 5, 0.4, 0.1, 5, 10);
-		amoeba.setDataForInexactMargin(0.05, 2.5, 0.2, 0.05, 5, 10);
+		//Dynamic errors
+		amoeba.setDataForErrorMargin(1000, 5, 0.4, 0.1, 40, 80);
+		amoeba.setDataForInexactMargin(500, 2.5, 0.2, 0.05, 40, 80);
+		
+		//amoeba.setDataForErrorMargin(100, 5, 0.4, 0.1, 10000, 20000);
+		//amoeba.setDataForInexactMargin(50, 2.5, 0.2, 0.05, 10000, 20000);
+		
+		//Static errors
+		/*amoeba.setDataForErrorMargin(5, 5, 0.4, 200, 5000, 100000);
+		amoeba.setDataForInexactMargin(2.5, 2.5, 0.2, 100, 5000, 100000);*/
+		
+		//amoeba.setDataForErrorMargin(200, 5, 0.4, 200, 5000, 100000);
+		//amoeba.setDataForInexactMargin(100, 2.5, 0.2, 100, 5000, 100000);
 		
 		/* Default */
 //		amoeba.setAVT_acceleration(2);
@@ -54,11 +64,11 @@ public class F_XY_Launcher implements Serializable {
 		amoeba.setGenerateCSV(false);
 		
 		/* This is the initialization of the studied system. It's only for the sake of example, not a part of AMOEBA initialization*/
+		//F_XY_ManagerSphere bcm = new F_XY_ManagerSphere(50.0);
 		F_XY_Manager bcm = new F_XY_Manager(50.0);
-		bcm.setWorld(amoeba.getScheduler().getWorld());
 		ArrayList<Percept> percepts = new  ArrayList<Percept>();
 		
-		for (int i = 0 ; i < 1000 ; i++) {
+		for (int i = 0 ; i < 10 ; i++) {
 
 			/* This is the studied system part. Feel free to use any data source.*/
 			bcm.playOneStep(0);

AMOEBA3/src/experiments/badContext/F_XY_Manager.java

@@ -30,7 +30,6 @@ public class F_XY_Manager implements StudiedSystem, Serializable{
 	double spaceSize;
 	
 	/** The world. */
-	World world;
 	Random generator;
 	
 	
@@ -79,14 +78,6 @@ public class F_XY_Manager implements StudiedSystem, Serializable{
 		
 	}
 	
-	/**
-	 * Sets the world.
-	 *
-	 * @param world the new world
-	 */
-	public void setWorld(World world) {
-		this.world = world;
-	}
 
 	
 

AMOEBA3/src/experiments/badContext/F_XY_ManagerSphere.java

+package experiments.badContext;
+
+import java.io.Serializable;
+import java.util.HashMap;
+import java.util.Random;
+
+import mas.agents.context.Context;
+import mas.agents.head.Head;
+import mas.kernel.StudiedSystem;
+import mas.kernel.World;
+
+// TODO: Auto-generated Javadoc
+/**
+ * The Class BadContextManager.
+ */
+public class F_XY_ManagerSphere implements StudiedSystem, Serializable{
+
+	/** The x. */
+	double x = 0;
+	
+	/** The y. */
+	double y = 0;
+	
+	/** The result. */
+	double result = 0;
+	
+	/** The first step. */
+	boolean firstStep = true;
+	
+	double spaceSize;
+	
+	/** The world. */
+	Random generator;
+	
+	
+	public F_XY_ManagerSphere(double size) {
+		this.spaceSize= size;
+	}
+	
+	
+	/* (non-Javadoc)
+	 * @see kernel.StudiedSystem#playOneStep(double)
+	 */
+	@Override
+	public void playOneStep(double action) {
+
+			
+		if (generator == null)	generator = new Random(29);
+			
+		
+		x = (generator.nextDouble() - 0.5) * spaceSize * 4;
+		y = (generator.nextDouble() - 0.5) * spaceSize * 4;
+	}
+
+	/* (non-Javadoc)
+	 * @see kernel.StudiedSystem#getOutput()
+	 */
+	@Override
+	public HashMap<String, Double> getOutput() {
+		HashMap<String, Double> out = new HashMap<String, Double>();
+
+		result = (Math.sqrt(x*x + y*y) < spaceSize) ? 2*x + y : 5*x - 8*y;
+		//result = (y > -spaceSize && y < spaceSize && x < spaceSize && x > -spaceSize) ? 2*x + y : 5*x - 8*y;
+		//result = (2*x) + (4*y) + x*y;
+	//	result = (x > 2*y) ? 0.0 : 1.0;
+		
+		out.put("px",x);
+		out.put("py",y);
+		out.put("oracle",result);
+		return out;
+	}
+
+	/* (non-Javadoc)
+	 * @see kernel.StudiedSystem#switchControlMode()
+	 */
+	@Override
+	public void switchControlMode() {
+		
+	}
+	
+
+	
+
+
+
+}
\ No newline at end of file

AMOEBA3/src/mas/agents/context/Context.java

@@ -35,7 +35,7 @@ public class Context extends AbstractContext implements Serializable{
 
 	ArrayList<Percept> perceptSenders = new ArrayList<Percept>();
 	
-	private Head controller;
+	private Head headAgent;
 	private HashMap<Percept, Range> ranges = new HashMap<Percept, Range>();
 	private ArrayList<Experiment> experiments = new ArrayList<Experiment>(); /*If memory is a concern, their is room for improvements here*/
 	
@@ -88,15 +88,15 @@ public class Context extends AbstractContext implements Serializable{
 	 * Builds the context.
 	 *
 	 * @param world the world
-	 * @param controller the controller
+	 * @param headAgent the headAgent
 	 */
-	private void buildContext (Head controller) {
+	private void buildContext (Head headAgent) {
 		
 		ArrayList<Percept> var = world.getAllPercept();
 		Experiment firstPoint = new Experiment();
-		this.controller = controller;
+		this.headAgent = headAgent;
 		
-		action = this.controller.getOracleValue();
+		action = this.headAgent.getOracleValue();
 		maxActivationsRequired = var.size();
 		
 		for (Percept v : var) {
@@ -113,7 +113,7 @@ public class Context extends AbstractContext implements Serializable{
 			v.addContextSortedRanges(this);
 		}
 		localModel = this.world.buildLocalModel(this);
-		firstPoint.setProposition(this.controller.getOracleValue());
+		firstPoint.setProposition(this.headAgent.getOracleValue());
 		experiments.add(firstPoint);
 		localModel.updateModel(this);
 		this.world.getScheduler().addAlteredContext(this);
@@ -163,7 +163,7 @@ public class Context extends AbstractContext implements Serializable{
 		   Range range = new Range(entry.getValue());
 		   this.ranges.put(percept, range);
 		}
-		this.controller = c.controller;
+		this.headAgent = c.headAgent;
 		this.action = c.action;
 		this.nSelection = c.nSelection;
 		this.bestContext = c.bestContext;
@@ -278,12 +278,12 @@ public class Context extends AbstractContext implements Serializable{
 		super.play();
 		
 		if(computeValidityByPercepts()) {
+			sendMessage(getActionProposal(), MessageType.PROPOSAL, headAgent);
+			Config.print("Message envoy", 4);
 			//System.out.println("Valid context by Percepts "+this.name);
 		}
 		
 		if (computeValidity()) {
-			sendMessage(getActionProposal(), MessageType.PROPOSAL, controller);
-			Config.print("Message envoy", 4);
 			//System.out.println("Valid context by Context "+this.name);
 		}
 		
@@ -298,7 +298,7 @@ public class Context extends AbstractContext implements Serializable{
 		//ENDO
 		for (Percept v : ranges.keySet()) {
 			if (ranges.get(v).isTooSmall()){
-				solveNCS_Uselessness(controller);
+				solveNCS_Uselessness(headAgent);
 				break;
 			}
 		}
@@ -354,7 +354,7 @@ public class Context extends AbstractContext implements Serializable{
 	 */
 	public void solveNCS_IncompetentHead(Head head) {
 		world.raiseNCS(NCS.HEAD_INCOMPETENT);
-		growRanges(head);
+		growRanges();
 	}
 	
 	/**
@@ -640,7 +640,7 @@ private Percept getPerceptWithLesserImpactOnVolume(ArrayList<Percept> containing
 	 * @return the controler
 	 */
 	public Head getControler() {
-		return controller;
+		return headAgent;
 	}
 
 	/**
@@ -649,7 +649,7 @@ private Percept getPerceptWithLesserImpactOnVolume(ArrayList<Percept> containing
 	 * @param controler the new controler
 	 */
 	public void setControler(Head controler) {
-		this.controller = controler;
+		this.headAgent = controler;
 	}
 
 	/**
@@ -676,7 +676,7 @@ private Percept getPerceptWithLesserImpactOnVolume(ArrayList<Percept> containing
 	@Override
 	public ArrayList<? extends Agent> getTargets() {
 		ArrayList<Agent> arrayList = new ArrayList<Agent>();
-		arrayList.add(controller);
+		arrayList.add(headAgent);
 		return arrayList;
 	}
 
@@ -931,7 +931,7 @@ private Percept getPerceptWithLesserImpactOnVolume(ArrayList<Percept> containing
 		for (Percept v : var) {
 			exp.addDimension(v, v.getValue());
 		}
-		exp.setProposition(controller.getOracleValue());
+		exp.setProposition(headAgent.getOracleValue());
 		
 		experiments.add(exp);
 		this.world.getScheduler().addAlteredContext(this);
@@ -971,12 +971,12 @@ private Percept getPerceptWithLesserImpactOnVolume(ArrayList<Percept> containing
 	 *
 	 * @param head the head
 	 */
-	public void growRanges(Head head) {
-		ArrayList<Percept> var = world.getAllPercept();
-		for (Percept v : var) {
-			boolean contain = ranges.get(v).contains(v.getValue()) == 0 ? true : false;
+	public void growRanges() {
+		ArrayList<Percept> allPercepts = world.getAllPercept();
+		for (Percept pct : allPercepts) {
+			boolean contain = ranges.get(pct).contains(pct.getValue()) == 0 ? true : false;
 			if (!contain) {
-				ranges.get(v).adapt(this, v.getValue(), v);
+				ranges.get(pct).adapt(this, pct.getValue(), pct);
 			}
 		}
 	}

AMOEBA3/src/mas/agents/head/Head.java

@@ -27,7 +27,9 @@ public class Head extends AbstractHead {
 	
 	//private BlackBoxAgent oracle;
 	
-	private ArrayList<Context> contexts = new ArrayList<Context>();
+	private ArrayList<Context> activatedContexts = new ArrayList<Context>();
+	private ArrayList<Context> partialyActivatedContexts = new ArrayList<Context>();
+	private ArrayList<Pair<Context,Context>> sharedIncompetenceContextPairs = new ArrayList<Pair<Context,Context>>();
 	private ArrayList<Double> xLastCriticityValues = new ArrayList<Double>();
 
 	
@@ -43,6 +45,7 @@ public class Head extends AbstractHead {
 	private int perfIndicatorInexact = 0;
 	
 	private double prediction;
+	private double endogenousPrediction;
 	private double oracleValue;
 	private double oldOracleValue;
 	private double criticity;
@@ -126,9 +129,13 @@ public class Head extends AbstractHead {
 		// contexts.clear();
 
 		if (m.getType() == MessageType.PROPOSAL) { // Value useless
-			contexts.add((Context) m.getSender());
+			activatedContexts.add((Context) m.getSender());
 		}
 	}
+	
+	public void addPartiallyActivatedContext(Context partialyactivatedContext) {
+		partialyActivatedContexts.add(partialyactivatedContext);
+	}
 
 	/**
 	 * The core method of the head agent.
@@ -136,7 +143,7 @@ public class Head extends AbstractHead {
 	 */
 	public void play() {
 
-		nPropositionsReceived = contexts.size();
+		nPropositionsReceived = activatedContexts.size();
 		newContextWasCreated = false;
 		setContextFromPropositionWasSelected(false);		
 		oldOracleValue = oracleValue;
@@ -158,9 +165,13 @@ public class Head extends AbstractHead {
 			//updateStatisticalInformations(); ///regarder dans le d彋ail, possible que ce pas trop utile
 		}
 		//中
+		
+		endogenousPlay();
+		
 		updateStatisticalInformations(); ///regarder dans le d彋ail, possible que ce pas trop utile
 		
-		contexts.clear();
+		activatedContexts.clear();
+		partialyActivatedContexts.clear();
 		newContext = null;
 		
 		System.out.println("@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ Error allowded :" + errorAllowed);
@@ -171,7 +182,7 @@ public class Head extends AbstractHead {
 	
 	private void playWithOracle() {
 			
-		if (contexts.size() > 0) {
+		if (activatedContexts.size() > 0) {
 			selectBestContext(); //using highest confidence 
 		}
 
@@ -207,7 +218,7 @@ public class Head extends AbstractHead {
 	 */
 	private void playWithoutOracle() {
 		
-		Config.print("Nombre de contexte : " + contexts.size(), 1);
+		Config.print("Nombre de contextes activ廥: " + activatedContexts.size(), 1);
 		
 		selectBestContext();
 		if (bestContext != this.lastUsedContext) {
@@ -228,6 +239,63 @@ public class Head extends AbstractHead {
 		criticity = Math.abs(oracleValue - prediction);
 	}
 	
+	private void endogenousPlay() {
+		
+		if(uniqueActivatedContext()) {
+			endogenousPrediction = activatedContexts.get(0).getActionProposal();
+		}
+		else {
+			endogenousPrediction = 0.0;
+		}
+		
+		
+		/*else if(severalActivatedContexts()){
+			NCS_EndogenousCompetition();
+		}
+		else {
+			if(surroundingContexts()) {
+				NCS_EndogenousSharedIncompetence();
+			}
+			else {
+				NCS_EndogenousIncompetence();
+			}
+		}*/
+	}
+	
+	
+	
+	private boolean uniqueActivatedContext() {
+		//Test if only one context is activated
+		return activatedContexts.size() == 1;
+	}
+	
+	private boolean severalActivatedContexts() {
+		//Test if several context are activated
+		return activatedContexts.size() > 1;
+	}
+	
+	private boolean surroundingContexts() {
+		//Test if there are surrounding contexts
+		
+		for(Context partiallyActivatedContext : partialyActivatedContexts) {
+			
+		}
+		return false;
+	}
+	
+	private void NCS_EndogenousCompetition() {
+		// Creation if twin contexts to give the endogenous prediction
+	}
+	
+	private void NCS_EndogenousSharedIncompetence() {
+		// Extrapolation of contexts by creating twin contexts that will give the prediction
+	}
+	
+	private void NCS_EndogenousIncompetence() {
+		// Extrapolation of contexts by creating twin contexts that will give the prediction
+	}
+	
+	
 	private void NCSDetection_Create_New_Context() {
 		/*Finally, head agent check the need for a new context agent*/
 		
@@ -250,10 +318,10 @@ public class Head extends AbstractHead {
 	private void NCSDetection_Concurrence() {
 		/*If result is good, shrink redundant context (concurrence NCS)*/
 		if (bestContext != null && criticity <= this.errorAllowed) {
-			for (int i = 0 ; i < contexts.size() ; i++) {
-				if (contexts.get(i) != bestContext && !contexts.get(i).isDying() && this.getCriticity(contexts.get(i)) <= 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) {
 			//		System.out.println("Shrink context " + contexts.get(i).getName());
-					contexts.get(i).solveNCS_Concurrence(this);
+					activatedContexts.get(i).solveNCS_Concurrence(this);
 				}
 			}
 		}
@@ -261,7 +329,7 @@ public class Head extends AbstractHead {
 	
 	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 (contexts.isEmpty() || (criticity > this.errorAllowed && !oneOfProposedContextWasGood())){
+		if (activatedContexts.isEmpty() || (criticity > this.errorAllowed && !oneOfProposedContextWasGood())){
 			ArrayList<Agent> allContexts = world.getScheduler().getContexts();
 			
 			Context c = getNearestGoodContext(allContexts);
@@ -282,8 +350,8 @@ public class Head extends AbstractHead {
 	
 	private void selfAnalysationOfContexts() {
 		/*All context which proposed itself must analyze its proposition*/
-		for (int i = 0 ; i < contexts.size() ; i++) {
-				contexts.get(i).analyzeResults(this);
+		for (int i = 0 ; i < activatedContexts.size() ; i++) {
+			activatedContexts.get(i).analyzeResults(this);
 		}
 	}
 	
@@ -414,7 +482,7 @@ public class Head extends AbstractHead {
 	 */
 	private boolean oneOfProposedContextWasGood() {
 		boolean b = false;
-		for (Context c : contexts) {
+		for (Context c : activatedContexts) {
 			if (oracleValue - c.getActionProposal() < errorAllowed) {
 				b = true;
 			}
@@ -467,7 +535,7 @@ public class Head extends AbstractHead {
 			xLastCriticityValues.remove(0);
 		}
 		
-		
+		System.out.println("@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ Average Prediction Criticity :" + averagePredictionCriticity);
 		
 		if (averagePredictionCriticity > errorAllowed) {
 			perfIndicator--;
@@ -532,8 +600,8 @@ public class Head extends AbstractHead {
 	 *
 	 * @return the contexts
 	 */
-	public ArrayList<Context> getContexts() {
-		return contexts;
+	public ArrayList<Context> getActivatedContexts() {
+		return activatedContexts;
 	}
 
 	/**
@@ -541,8 +609,8 @@ public class Head extends AbstractHead {
 	 *
 	 * @param contexts the new contexts
 	 */
-	public void setContexts(ArrayList<Context> contexts) {
-		this.contexts = contexts;
+	public void setActivatesContexts(ArrayList<Context> contexts) {
+		this.activatedContexts = contexts;
 	}
 
 
@@ -552,14 +620,14 @@ public class Head extends AbstractHead {
 	private void selectBestContext() {
 		
 		Context bc;
-		if (contexts.isEmpty()) {
+		if (activatedContexts.isEmpty()) {
 			bc = lastUsedContext;
 		} else {
-			bc = contexts.get(0);
+			bc = activatedContexts.get(0);
 		}
 		double currentConfidence = Double.NEGATIVE_INFINITY;
 
-		for (Context context : contexts) {
+		for (Context context : activatedContexts) {
 			if (context.getConfidence() > currentConfidence) {
 				bc  = context;
 				currentConfidence = bc.getConfidence();
@@ -591,17 +659,10 @@ public class Head extends AbstractHead {
 	 */
 	@Override
 	public ArrayList<? extends Agent> getTargets() {
-		return contexts;
+		return activatedContexts;
 	}
 
-	/**
-	 * Gets the active contexts.
-	 *
-	 * @return the active contexts
-	 */
-	public ArrayList<Context> getActiveContexts() {
-		return contexts;
-	}
+
 	
 	/**
 	 * Gets the criticity.

AMOEBA3/src/mas/agents/head/Pair.java

+package mas.agents.head;
+
+public class Pair<L,R> {
+
+	private L l;
+    private R r;
+    public Pair(L l, R r){
+        this.l = l;
+        this.r = r;
+    }
+    public L getL(){ return l; }
+    public R getR(){ return r; }
+    public void setL(L l){ this.l = l; }
+    public void setR(R r){ this.r = r; }
+	
+}

AMOEBA3/src/mas/kernel/AMOEBA.java

@@ -516,6 +516,12 @@ public class AMOEBA extends Thread {
 		scheduler.getWorld().setAVT_percentAtStart(aVT_percentAtStart);
 	}
 	
-
+	public double getAveragePredictionCriticity() {
+		return scheduler.getHeadAgent().getAveragePredictionCriticity();
+	}
+	
+	public double getNumberOfContextAgents() {
+		return scheduler.getContexts().size();
+	}
 
 }
\ No newline at end of file

AMOEBA3/src/visualization/view/global/PanelOneChart.java

+package visualization.view.global;
+
+import java.awt.FlowLayout;
+
+import javax.swing.JPanel;
+
+import mas.kernel.World;
+import mas.ncs.NCS;
+
+import org.jfree.chart.ChartPanel;
+import org.jfree.chart.JFreeChart;
+import org.jfree.chart.axis.AxisLocation;
+import org.jfree.chart.axis.NumberAxis;
+import org.jfree.chart.plot.CombinedDomainXYPlot;
+import org.jfree.chart.plot.PlotOrientation;
+import org.jfree.chart.plot.XYPlot;
+import org.jfree.chart.renderer.xy.StandardXYItemRenderer;
+import org.jfree.chart.renderer.xy.XYItemRenderer;
+import org.jfree.data.xy.XYDataset;
+import org.jfree.data.xy.XYSeries;
+import org.jfree.data.xy.XYSeriesCollection;
+
+import visualization.view.system.ScheduledItem;
+
+// TODO: Auto-generated Javadoc
+/**
+ * The Class PanelChart.
+ */
+public class PanelOneChart extends JPanel implements ScheduledItem {
+
+	/** The chart panel agents. */
+	/* Agents chart */
+	ChartPanel chartPanel;
+	
+	/** The chart agents. */
+	JFreeChart chart;
+	
+	/** The data set agents. */
+	XYSeriesCollection dataSetPredictions;
+
+	
+	
+	/** The world. */
+	World world;
+
+	/**
+	 * Instantiates a new panel chart.
+	 *
+	 * @param world the world
+	 */
+	public PanelOneChart(World world) {
+
+		this.setLayout(new FlowLayout());
+		this.world = world;
+
+		/* Create prediction chart */
+		dataSetPredictions = createDataSetPredictions();
+		JFreeChart chart = createChart();
+		chartPanel = new ChartPanel(chart);
+		chartPanel.setPreferredSize(new java.awt.Dimension(600, 400));
+
+
+
+	}
+
+	/*
+	 * private JFreeChart createChart(DefaultCategoryDataset dataset2) { // TODO
+	 * Auto-generated method stub return null; }
+	 * 
+	 * private DefaultCategoryDataset createDataset() { // TODO Auto-generated
+	 * method stub return null; }
+	 */
+
+	/**
+	 * Creates the data set agents.
+	 *
+	 * @return the XY series collection
+	 */
+	private XYSeriesCollection createDataSetPredictions() {
+
+		XYSeriesCollection collection = new XYSeriesCollection();
+
+		collection.addSeries(new XYSeries("Predictions"));
+		collection.addSeries(new XYSeries("Endogenous Predictions"));
+
+		return collection;
+
+	}
+
+
+
+	/**
+	 * Creates the chart.
+	 *
+	 * @return the j free chart
+	 */
+	private JFreeChart createChart() {
+
+		// create subplot 1...
+		final XYDataset data1 = dataSetPredictions;
+		final XYItemRenderer renderer1 = new StandardXYItemRenderer();
+		final NumberAxis rangeAxis1 = new NumberAxis("Agents in AMAS");
+		final XYPlot subplot1 = new XYPlot(data1, null, rangeAxis1, renderer1);
+		subplot1.setRangeAxisLocation(AxisLocation.BOTTOM_OR_LEFT);
+
+		// parent plot...
+		final CombinedDomainXYPlot plot = new CombinedDomainXYPlot(
+				new NumberAxis("Tick"));
+		plot.setGap(10.0);
+
+		// add the subplots...
+		plot.add(subplot1, 1);
+		plot.setOrientation(PlotOrientation.VERTICAL);
+
+		// return a new chart containing the overlaid plot...
+		return new JFreeChart(" Agents in AMAS",
+				JFreeChart.DEFAULT_TITLE_FONT, plot, true);
+	}
+
+	
+
+	/* (non-Javadoc)
+	 * @see view.system.ScheduledItem#update()
+	 */
+	@Override
+	public void update() {
+
+		int tick = world.getScheduler().getTick();
+		
+		dataSetPredictions.getSeries("Predictions").add(
+				tick, world.getNumberOfAgents().get("Context"));
+		dataSetPredictions.getSeries("Endogenous Predictions").add(
+				tick, world.getNumberOfAgents().get("Percept"));
+
+
+		
+		
+
+	}
+
+	// }
+
+}

AMOEBA3/src/visualization/view/system/MainTabbedPanel.java

@@ -11,6 +11,7 @@ import visualization.log.ConsolePanel;
 import visualization.observation.Observation;
 import visualization.view.blackbox.BlackBoxPanel;
 import visualization.view.global.PanelChart;
+import visualization.view.global.PanelOneChart;
 import visualization.view.system.nDim.PanelParallelCoordinates;
 import visualization.view.system.twoDim.GrapheTwoDimPanelStandard;
 import mas.blackbox.BlackBox; 
@@ -33,6 +34,7 @@ public class MainTabbedPanel extends JTabbedPane{
 	
 	/** The panel chart. */
 	private PanelChart panelChart;
+	private PanelOneChart exoVsEndoChart;
 	
 	/** The panel two dim standard. */
 	private GrapheTwoDimPanelStandard panelTwoDimStandard;
@@ -79,8 +81,10 @@ public class MainTabbedPanel extends JTabbedPane{
 		panelTwoDimStandard = new GrapheTwoDimPanelStandard(world);
 		panelParallelCoordinates = new PanelParallelCoordinates(world);
 		consolePanel = new ConsolePanel();
+		exoVsEndoChart = new PanelOneChart(world);
 		
 		world.getScheduler().addScheduledItem(panelChart);
+		world.getScheduler().addScheduledItem(exoVsEndoChart);
 		
 		//this.addTab("BlackBox", new JScrollPane(blackBoxPanel,JScrollPane.VERTICAL_SCROLLBAR_ALWAYS,JScrollPane.HORIZONTAL_SCROLLBAR_ALWAYS));
 		//this.addTab("System", systemPanel);
@@ -90,6 +94,7 @@ public class MainTabbedPanel extends JTabbedPane{
 	//	this.addTab("TwoDim", new JScrollPane(panelTwoDim,JScrollPane.VERTICAL_SCROLLBAR_ALWAYS,JScrollPane.HORIZONTAL_SCROLLBAR_ALWAYS));
 	//	this.addTab("TwoDim", panelTwoDim);
 		this.addTab("Console", new JScrollPane(consolePanel,JScrollPane.VERTICAL_SCROLLBAR_ALWAYS,JScrollPane.HORIZONTAL_SCROLLBAR_ALWAYS));
+		this.addTab("Exo VS endo", new JScrollPane(exoVsEndoChart,JScrollPane.VERTICAL_SCROLLBAR_ALWAYS,JScrollPane.HORIZONTAL_SCROLLBAR_ALWAYS));
 		
 		((Frame) this.getTopLevelAncestor()).pack();
 	}