A Python implementation of artificial intelligence search algorithms to solve problems within the Berkeley Pac-Man environment. The Pac-Man Projects, developed at UC Berkeley, apply Artificial Intelligence concepts to the famous arcade game.
Under The Supervision of Prof.Mahdi Javanmardi
Fall 2021
1. Search
Implemented Depth First Search (DFS), Breadth First Search (BFS), Uniform Cost Search, A* Search Algorithms.
2. Multi Agent Search
Implemented Multiagent, Minimax, Alpha-Beta pruning and Expectimax algorithms.
3. Reinforcement Learning
Implement model-based and model-free reinforcement learning algorithms.
Includes Value Iteration, Bridge Crossing Analysis, Policies, Q-Learning, Epsilon Greedy, Bridge Crossing Revisited, Q-Learning and Approximate Q-Learning