AI-Powered Checkers

Overview:

This project was done during my Principles of AI class (COM S 472) at Iowa State University. The goal of this project was to implement checkers using python and explore various algorithms for the computer to play its turn. After that, we would compare the results.

Methods:

• Random Search: This method served as a baseline, providing insights into AI performance without a specific strategy.
• Alpha-Beta Search Algorithms: I implemented two variants of the Alpha-Beta search algorithm. These intelligent algorithms significantly improved the AI agents’ decision-making by efficiently exploring possible game states.

Results:

The Alpha-Beta search algorithms empowered the AI agents to be much more successful than the other method. After comparing against the baseline, I also compared the 2 search methods to find the stronger AI. One of the really enjoyable things about this project was at the end, we had a game to play against to see how it does against a human. While humans could still beat this basic AI, it showed the basics of how AI can dominate people in these types of games.