The Pacman Projects by the University of California, Berkeley.

In this project, Pacman agent will find paths through his maze world, both to reach a particular location and to collect food efficiently. Try to build general search algorithms and apply them to Pacman scenarios.

This contains Pac-Man projects which were adopted from UC Berkeley's introductory artificial intelligence class, CS 188. It explores several techniques of Artificial Intelligence such as Searching, Heuristics, Adversarial Behaviour, Reinforcement Learning etc.

Project 1: Search - DFS, BFS, UCS, Greedy Search, A* Search

Project 2: MultiAgent - minimax, alpha-beta pruning, expectimax

Project 3: Markov Decision Processes & Reinforcement Learning - Value Iteration, Q-learning, Approximate Q-learning

Project 4: Ghostbusters - Hidden Markov Model, Bayes Net, Particle Filtering.

Detailed information about each of this project can be found under each project's folder.