Project Summery

The Pac-Man projects were developed for UC Berkeley's introductory artificial intelligence course, CS 188. They apply an array of AI techniques to playing Pac-Man.

Search: I implemented depth-first, breadth-first, uniform cost, and A* search algorithms. These algorithms are used to solve navigation and traveling salesman problems in the Pacman world.

Multiagent Search: Classic Pacman is modeled as both an adversarial and a stochastic search problem. I implement multiagent minimax and expectimax algorithms, as well as designing evaluation functions.

Reinforcement Learning: In this part I implement model-based and model-free reinforcement learning algorithms, applied to the AIMA textbook's Gridworld, Pacman, and a simulated crawling robot.