The Berkeley Pacman Projects repository offers a modular Python codebase where users build and test AI agents in a Pacman maze. It guides learners through uninformed and informed search (DFS, BFS, A*), adversarial multi-agent search (minimax, alpha-beta pruning), and reinforcement learning (Q-learning with feature extraction). Integrated graphical interfaces visualize agent behavior in real time, while built-in test cases and an autograder verify correctness. By iterating on algorithm implementations, users gain practical experience in state space exploration, heuristic design, adversarial reasoning, and reward-based learning within a unified game framework.

Halite II is an open-source challenge framework that hosts turn-based strategy matches between user-written bots. Each turn, agents receive a map state, issue movement and attack commands, and compete to control the most territory. The platform includes a game server, map parser, and visualization tool. Developers can test locally, refine heuristics, optimize performance under time constraints, and submit to an online leaderboard. The system supports iterative bot improvements, multi-agent cooperation, and custom strategy research in a standardized environment.