This is the second project of the Spring 2014 CS 188 (Introduction to Artificial Intelligence) class at UC Berkeley. It implements a pacman which can play against adversarial agents with dynamic tree look up (both Minimax and Expectimax). It optimizes tree lookup with AlphaBetaPruning and finally contains a master strategy in the form of the betterEvaluationFunction (in multiAgents.py) for evaluating each state in the tree.
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This is the second project of the Spring 2014 CS 188 (Introduction to Artificial Intelligence) class at UC Berkeley. It implements a pacman who can play against adversarial agents with dynamic tree look up (both Minimax and Expectimax). it optimizes tree lookup with AlphaBetaPruning and finally contains a master strategy in the form of the bette...
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Jornason/multiAgentPacman
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This is the second project of the Spring 2014 CS 188 (Introduction to Artificial Intelligence) class at UC Berkeley. It implements a pacman who can play against adversarial agents with dynamic tree look up (both Minimax and Expectimax). it optimizes tree lookup with AlphaBetaPruning and finally contains a master strategy in the form of the bette...
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