Adds Decision Network

Author: samagra14

aima-core/src/main/java/aima/core/probability/DecisionNetwork.java

@@ -1,27 +1,42 @@
 package aima.core.probability;
 
+import aima.core.probability.bayes.BayesInference;
 import aima.core.probability.bayes.BayesianNetwork;
 import aima.core.probability.domain.FiniteDomain;
+import aima.core.probability.proposition.AssignmentProposition;
 import org.junit.Test;
 
+import java.util.List;
+
 public abstract class DecisionNetwork {
 
     private BayesianNetwork network;
     private RandomVariable action;
+    private BayesInference inferenceProcedure;
+
+    public DecisionNetwork(BayesianNetwork network,
+                           RandomVariable action, BayesInference inferenceProcedure) {
+        this.network = network;
+        this.action = action;
+        this.inferenceProcedure = inferenceProcedure;
+    }
 
     public abstract double getUtilityForAction(RandomVariable action, Object value );
 
-    public Object getBestAction(){
-        double maxUtilValue = Double.MIN_VALUE;
-        Object actionValue = null;
+    public double getExpectedUtility(RandomVariable action,
+                                     List<AssignmentProposition> evidence){
+        double utility = 0;
+        CategoricalDistribution distribution = inferenceProcedure.ask((new RandomVariable[]{action}),
+                ((AssignmentProposition[])evidence.toArray()),this.getNetwork());
         for (Object value :
                 ((FiniteDomain) action.getDomain()).getPossibleValues()) {
-            if (maxUtilValue < getUtilityForAction(action,value)){
-                maxUtilValue = getUtilityForAction(action,value);
-                actionValue = value;
-            }
+            utility += distribution.getValue(value)*this.getUtilityForAction(action,value);
         }
-        return actionValue;
+        return utility;
+    }
+
+    public Object getBestAction(){
+        return action;
     }
 
     public BayesianNetwork getNetwork() {

aima-core/src/main/java/aima/core/probability/InformationGatheringAgent.java

@@ -9,6 +9,7 @@
 import aima.core.probability.proposition.AssignmentProposition;
 
 import java.util.ArrayList;
+import java.util.Arrays;
 import java.util.Collections;
 import java.util.List;
 
@@ -58,10 +59,20 @@ private List<Double> vpiPerUnitCost(List<RandomVariable> variablesInTopologicalO
     protected abstract double getCost(RandomVariable var);
 
     protected double getVpi(RandomVariable var){
+        double vpi =0;
+        CategoricalDistribution distribution = inferenceMethod.ask((new RandomVariable[]{var}),
+                ((AssignmentProposition[])observedEvidence.toArray()),decisionNetwork.getNetwork());
         for (Object value :
                 ((FiniteDomain) var.getDomain()).getPossibleValues()) {
-            inferenceMethod.ask()
+            double posterierProb = distribution.getValue(value);
+            List<AssignmentProposition> modifiedEvidence = new ArrayList<>(observedEvidence);
+            modifiedEvidence.add(new AssignmentProposition(var,value));
+            double expectedUtilityForParticularValue = decisionNetwork.getExpectedUtility(var,
+                    modifiedEvidence);
+            vpi+= posterierProb*expectedUtilityForParticularValue;
         }
+        vpi-=decisionNetwork.getExpectedUtility(var,observedEvidence);
+        return vpi;
     }
 
     abstract List<AssignmentProposition> integratePercept(List<AssignmentProposition> observedEvidence, Percept percept);