iliasmentz/Berkeley-CS-188-AI-Pacman
My implementation for Berkeley AI Pacman projects No. 1 and No. 2
This project offers an implementation for various artificial intelligence search algorithms within the classic Pacman game environment. It takes the game's state as input and outputs the optimal moves for Pacman to achieve specific goals, such as finding food or navigating mazes. This is primarily for students or educators in AI courses looking for examples of search and multi-agent systems.
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Use this if you are studying or teaching AI and want to see practical applications of search algorithms (BFS, DFS, A*) and multi-agent decision-making (Minimax, Expectimax) in a familiar game context.
Not ideal if you are looking for a tool to develop commercial game AI or a general-purpose AI library for real-world applications beyond academic examples.
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Python
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Oct 28, 2019
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