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qlearningAgents.py ( original ) # qlearningAgents.py # ------------------ # Licensing Information: Please do not distribute or publish solutions to this # project. You are free to use and extend these projects for educational # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by # John DeNero ([email protected]) and Dan Klein ([email protected]). # For more info, see from game import * from learningAgents import ReinforcementAgent from featureExtractors import * import random , util , math class QLearningAgent ( ReinforcementAgent ): """ Q-Learning Agent Functions you should fill in: - getQValue - getAction - getValue - getPolicy - update Instance variables you have access to - self.epsilon (exploration prob) - self.alpha (learning rate) - self.discount (discount rate) Functions you should use - self.getLegalActions(state) which returns legal actions for a state """ def __init__ ( self , ** args ): "You can initialize Q-values here..." ReinforcementAgent . __init__ ( self , ** args ) "*** YOUR CODE HERE ***" def getQValue ( self , state , action ): """ Returns Q(state,action) Should return 0.0 if we never seen
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  • Summer '17
  • ASDF
  • Subroutine, Dan Klein

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Christopher Reinemann
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— Christopher R., University of Rhode Island '15, Course Hero Intern

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