This is a intro to AI project created by UC Berkeley that simulates the game of pacman, meant to teach foundational AI concepts. This project contains my implementation of the multi agent search problem, where I designed a pacman agent using mini max, alpha beta pruning, and expectimax algorithms. Pacman will choose the action that maximizes its own expected utility against ghost agents utilities, based on all possible outcomes.
Link to Project definition: https://ai.berkeley.edu/multiagent.html