Add a new batch algorithm (PSO)

msi.gama.core/.classpath

@@ -1,19 +1,19 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<classpath>
-	<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/JavaSE-11">
-		<attributes>
-			<attribute name="module" value="true"/>
-		</attributes>
-		<accessrules>
-			<accessrule kind="accessible" pattern="*/**"/>
-		</accessrules>
-	</classpathentry>
-	<classpathentry kind="con" path="org.eclipse.pde.core.requiredPlugins"/>
-	<classpathentry kind="src" path="src"/>
-	<classpathentry kind="src" path="gaml">
-		<attributes>
-			<attribute name="optional" value="true"/>
-		</attributes>
-	</classpathentry>
-	<classpathentry kind="output" path="bin"/>
-</classpath>
+<?xml version="1.0" encoding="UTF-8"?>
+<classpath>
+	<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/JavaSE-11">
+		<attributes>
+			<attribute name="module" value="true"/>
+		</attributes>
+		<accessrules>
+			<accessrule kind="accessible" pattern="*/**"/>
+		</accessrules>
+	</classpathentry>
+	<classpathentry kind="con" path="org.eclipse.pde.core.requiredPlugins"/>
+	<classpathentry kind="src" path="src"/>
+	<classpathentry kind="src" path="gaml">
+		<attributes>
+			<attribute name="optional" value="true"/>
+		</attributes>
+	</classpathentry>
+	<classpathentry kind="output" path="bin"/>
+</classpath>

msi.gama.core/src/msi/gama/kernel/batch/HillClimbing.java

@@ -147,7 +147,7 @@ public ParametersSet findBestSolution(final IScope scope) throws GamaRuntimeExce
 	// public void initializeFor(final IScope scope, final BatchAgent agent) throws GamaRuntimeException {
 	// super.initializeFor(scope, agent);
 	// }
-
+ 
 	@Override
 	protected void initParams(final IScope scope) {
 		final IExpression maxItExp = getFacet(ITER_MAX);

msi.gama.core/src/msi/gama/kernel/batch/InitializationUniform.java

@@ -43,7 +43,7 @@ public List<Chromosome> initializePop(final IScope scope, final List<IParameter.
 		if (algo.isMaximize) {
 			Collections.reverse(populationInitOrd);
 		}
-		return populationInitOrd.subList(0, populationDim);
+		return populationInitOrd.subList(0, populationDim - 1);
 	}
 
 }

msi.gama.core/src/msi/gama/kernel/batch/ParamSpaceExploAlgorithm.java

@@ -43,7 +43,7 @@ public abstract class ParamSpaceExploAlgorithm extends Symbol implements IExplor
 	public final static String[] COMBINATIONS = new String[] { "maximum", "minimum", "average" };
 	@SuppressWarnings ("rawtypes") public static final Class[] CLASSES =
 			{ GeneticAlgorithm.class, SimulatedAnnealing.class, HillClimbing.class, TabuSearch.class,
-					TabuSearchReactive.class, ExhaustiveSearch.class };
+					TabuSearchReactive.class, ExhaustiveSearch.class, Swarm.class};
 
 	static {
 		AbstractGamlAdditions._constants(COMBINATIONS);
@@ -55,8 +55,8 @@ public abstract class ParamSpaceExploAlgorithm extends Symbol implements IExplor
 	protected boolean isMaximize;
 	protected BatchAgent currentExperiment;
 	// protected IScope scope;
-	private ParametersSet bestSolution = null;
-	private Double bestFitness = null;
+	protected ParametersSet bestSolution = null;
+	protected Double bestFitness = null;
 	protected short combination;
 
 	protected abstract ParametersSet findBestSolution(IScope scope) throws GamaRuntimeException;
@@ -78,7 +78,7 @@ protected void initializeTestedSolutions() {
 		testedSolutions = new HashMap<ParametersSet, Double>();
 	}
 
-	void initParams() {
+	protected void initParams() {
 		GAMA.run(new InScope.Void() {
 
 			@Override
@@ -88,7 +88,7 @@ public void process(final IScope scope) {
 		});
 	}
 
-	void initParams(final IScope scope) {}
+	protected void initParams(final IScope scope) {}
 
 	public ParamSpaceExploAlgorithm(final IDescription desc) {
 		super(desc);
@@ -122,7 +122,7 @@ public void run(final IScope scope) {
 	@Override
 	public void setChildren(final Iterable<? extends ISymbol> commands) {}
 
-	protected boolean isMaximize() {
+	public boolean isMaximize() {
 		return isMaximize;
 	}
 
@@ -145,6 +145,7 @@ public Object value() {
 		});
 	}
 
+
 	@Override
 	public Double getBestFitness() {
 		return bestFitness;

msi.gama.core/src/msi/gama/kernel/batch/Particle.java

@@ -0,0 +1,135 @@
+package msi.gama.kernel.batch;
+
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+import msi.gama.kernel.experiment.BatchAgent;
+import msi.gama.kernel.experiment.IParameter;
+import msi.gama.kernel.experiment.ParametersSet;
+import msi.gama.metamodel.shape.GamaPoint;
+import msi.gama.runtime.IScope;
+import msi.gaml.operators.Cast;
+
+/**
+ * Represents a particle from the Particle Swarm Optimization algorithm.
+ */
+class Particle {
+
+    private ParametersSet position;        // Current position.
+    private ParametersSet velocity;
+    private ParametersSet bestPosition;    // Personal best solution.
+    private double bestEval;        // Personal best value.
+
+	protected HashMap<ParametersSet, Double> testedSolutions;
+
+	BatchAgent currentExperiment;
+	final Map<String, GamaPoint> parameters;
+
+	ParamSpaceExploAlgorithm algo;
+    /**
+     * Construct a Particle with a random starting position.
+     * @param beginRange    the minimum xyz values of the position (inclusive)
+     * @param endRange      the maximum xyz values of the position (exclusive)
+     */
+    Particle (IScope scope, BatchAgent agent, ParamSpaceExploAlgorithm algorithm, HashMap<ParametersSet, Double> testedSolutionsMap) {
+        currentExperiment = agent;
+        algo = algorithm;
+        this.testedSolutions = testedSolutionsMap;
+        final List<IParameter.Batch> v = agent.getParametersToExplore();
+        parameters = new HashMap<>();
+        for (IParameter p : v ) {
+        	GamaPoint minMax = new GamaPoint(
+        			p.getMinValue(scope) != null ? Cast.asFloat(scope,p.getMinValue(scope)) : Double.NEGATIVE_INFINITY,
+        			p.getMaxValue(scope) != null ? Cast.asFloat(scope,p.getMaxValue(scope)) : Double.POSITIVE_INFINITY);
+        	parameters.put(p.getName(),minMax);
+        }
+		position = new ParametersSet(scope, v, true);
+        velocity = new ParametersSet(scope, v, true); 
+        bestPosition = new ParametersSet(velocity);
+        bestEval = eval();
+    }
+
+    /**
+     * The evaluation of the current position.
+     * @return      the evaluation
+     */
+    private double eval () {
+    	Double fitness = testedSolutions.get(position);
+		if (fitness == null) {
+			fitness = currentExperiment.launchSimulationsWithSolution(position);
+		}
+		testedSolutions.put(position, fitness);
+
+		/**/
+
+		return fitness.doubleValue();
+    }
+
+    /**
+     * Update the personal best if the current evaluation is better.
+     */
+    void updatePersonalBest () {
+        double eval = eval();
+        if (algo.isMaximize() && eval > bestEval
+				|| !algo.isMaximize() && eval < bestEval) {
+        	bestEval = eval;
+        	bestPosition = new ParametersSet(position);
+        }
+    }
+
+    /**
+     * Get the position of the particle.
+     * @return  the x position
+     */
+    ParametersSet getPosition () {
+        return position;
+    }
+
+    /**
+     * Getthe velocity of the particle.
+     * @return  the velocity
+     */
+    ParametersSet getVelocity () {
+        return velocity;
+    }
+
+    /**
+     * Get  the personal best solution.
+     * @return  the best position
+     */
+    ParametersSet getBestPosition() {
+        return bestPosition;
+    }
+
+    /**
+     * Get the value of the personal best solution.
+     * @return  the evaluation
+     */
+    double getBestEval () {
+        return bestEval;
+    }
+
+    /**
+     * Update the position of a particle by adding its velocity to its position.
+     */
+    void updatePosition (IScope scope) {
+
+      	for (String key : position.keySet()) {
+      		GamaPoint p = parameters.get(key);
+      		double val =  Cast.asFloat(scope, position.get(key)) + Cast.asFloat(scope, velocity.get(key));
+      		val = Math.min(Math.max(val, Cast.asFloat(scope, p.x)), p.y);
+      		position.put(key, val );
+      	}
+    }
+
+    /**
+     * Set the velocity of the particle.
+     * @param velocity  the new velocity
+     */
+    void setVelocity (ParametersSet velocity) {
+        this.velocity = velocity;
+    }
+
+
+}

msi.gama.core/src/msi/gama/kernel/batch/SelectionBest.java

@@ -31,6 +31,6 @@ public List<Chromosome> select(final IScope scope, final List<Chromosome> popula
 		if (maximize) {
 			Collections.reverse(nextGen);
 		}
-		return nextGen.subList(0, populationDim);
+		return nextGen.subList(0, populationDim - 1);
 	}
 }