Approximate QLearning Agent

qlearningAgents.py

@@ -190,15 +190,22 @@ class ApproximateQAgent(PacmanQAgent):
           Should return Q(state,action) = w * featureVector
           where * is the dotProduct operator
         """
-        "*** YOUR CODE HERE ***"
-        util.raiseNotDefined()
+        features = self.featExtractor.getFeatures(state, action)
+        qVal = 0
+        for feat, val in features.items():
+            qVal += val * self.weights[feat]
+        return qVal
 
     def update(self, state, action, nextState, reward):
         """
            Should update your weights based on transition
         """
         "*** YOUR CODE HERE ***"
-        util.raiseNotDefined()
+        features = self.featExtractor.getFeatures(state, action)
+        difference = (reward + self.discount * self.getValue(nextState)) - self.getQValue(state, action)
+        for feat, val in features.items():
+            self.weights[feat] += self.alpha * difference * val
+
 
     def final(self, state):
         "Called at the end of each game."