Welcome to the repository for our INFO6205 final project, where we dive into the fascinating world of Artificial Intelligence in board games with a focus on Othello. This project harnesses the power of the Monte Carlo Tree Search (MCTS) algorithm to strategize and compete in the classic game of Othello. Explore our innovative approach to MCTS, witness the algorithm's decision-making in real-time, and delve into the depths of AI in gaming.

To get started with the game and experience the MCTS algorithm in action, follow these simple steps:

1. Clone the Repository

   git clone https://github.com/<your-username>/INFO6205-final-project.git
   

2. Navigate to the Project Directory

   cd INFO6205-final-project
   

3. Compile the Source Code
   • Ensure you have Maven installed and run:

   mvn clean install
   

4. Run the Game
   • After successful compilation, start the game using:

   java -jar target/othello-mcts.jar
   

5. Enjoy Playing Othello
   • Interact with the game interface to play against the MCTS-powered AI or watch the AI play against itself.

For a comprehensive understanding of the project's findings, performance benchmarks, and insights into the MCTS algorithm's application in Othello, please refer to our detailed report: MCTS Game Algorithm Report.

Thank you for your interest in our project. We invite you to explore the complexities of AI in board gaming and contribute to the ongoing development and optimization of game strategies.

This project is licensed under the Apache License. See the LICENSE file for details.