Class Projects

1) Monte Carlo Tree Search Bot

In this project, we worked on developing a Monte Carlo Tree Search Bot to play against users in both Tic-Tac-Toe and Othello. At its core, MCTS embodies a principled approach to decision-making, iteratively exploring the game tree through a combination of random simulation and statistical analysis. By simulating thousands of possible game trajectories and selecting promising moves based on their expected outcomes, MCTS aims to craft winning strategies while adapting dynamically to evolving game states. Its ability to adapt and make strategic moves sets it apart, making MCTS an attractive candidate for AI-driven Tic-Tac-Toe and Othello gameplay. Codes