# valueIterationAgents.py # ----------------------- # Licensing Information: You are free to use or extend these projects for # educational purposes provided that (1) you do not distribute or publish # solutions, (2) you retain this notice, and (3) you provide clear # attribution to UC Berkeley, including a link to http://ai.berkeley.edu. # # Attribution Information: The Pacman AI projects were developed at UC Berkeley. # The core projects and autograders were primarily created by John DeNero # (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu). # Student side autograding was added by Brad Miller, Nick Hay, and # Pieter Abbeel (pabbeel@cs.berkeley.edu). import mdp, util from learningAgents import ValueEstimationAgent class ValueIterationAgent(ValueEstimationAgent): """ * Please read learningAgents.py before reading this.* A ValueIterationAgent takes a Markov decision process (see mdp.py) on initialization and runs value iteration for a given number of iterations using the supplied discount factor. """ def __init__(self, mdp, discount = 0.9, iterations = 100): """ Your value iteration agent should take an mdp on construction, run the indicated number of iterations and then act according to the resulting policy. Some useful mdp methods you will use: mdp.getStates() mdp.getPossibleActions(state) mdp.getTransitionStatesAndProbs(state, action) mdp.getReward(state, action, nextState) mdp.isTerminal(state) """ self.mdp = mdp self.discount = discount self.iterations = iterations self.values = util.Counter() # A Counter is a dict with default 0 # Write value iteration code here "*** YOUR CODE HERE ***" def getValue(self, state): """ Return the value of the state (computed in __init__). """ return self.values[state] def computeQValueFromValues(self, state, action): """ Compute the Q-value of action in state from the value function stored in self.values. """ "*** YOUR CODE HERE ***" util.raiseNotDefined() def computeActionFromValues(self, state): """ The policy is the best action in the given state according to the values currently stored in self.values. You may break ties any way you see fit. Note that if there are no legal actions, which is the case at the terminal state, you should return None. """ "*** YOUR CODE HERE ***" util.raiseNotDefined() def getPolicy(self, state): return self.computeActionFromValues(state) def getAction(self, state): "Returns the policy at the state (no exploration)." return self.computeActionFromValues(state) def getQValue(self, state, action): return self.computeQValueFromValues(state, action)