Oana Istoc | Pacman

Algorithms

Search Algorithms Implement depth-first, breadth-first, uniform cost, and A* search algorithms. These algorithms are designed to solve navigation and traveling salesman problems within the Pacman world.
Multi-Agent Search Classic Pacman is modeled as both an adversarial and a stochastic search problem. Implement multi-agent minimax and expectimax algorithms, along with the design of effective evaluation functions to enhance Pacman's decision-making capabilities.

Reinforcement Learning Explore the realm of reinforcement learning by implementing model-based and model-free algorithms. Apply these algorithms to scenarios in the AIMA textbook's Gridworld, Pacman, and a simulated crawling robot. Witness the learning process and adaptive behaviors in various environments.

Pacman AI Algorithms

Algorithms