Here's a README file for an AI-based Othello game implemented in a Python Jupyter Notebook:

This project is an implementation of the classic Othello (also known as Reversi) board game, where you can play against an AI opponent. The game is implemented in Python and designed to be run within a Jupyter Notebook.

• Interactive Gameplay: Play Othello against a computer AI within a Jupyter Notebook.
• AI Opponent: The AI uses a Minimax algorithm with optional alpha-beta pruning to provide a challenging gameplay experience.
• Visualization: The game board is visualized using Python's matplotlib, allowing for a clear and interactive representation of the game state.
• Customizable AI Difficulty: Adjust the depth of the AI's decision-making process to increase or decrease difficulty.

• Python 3
• Jupyter Notebook
• Required Python Libraries:
  • numpy
  • matplotlib

You can install the required libraries using pip:

pip install numpy matplotlib

1. Clone the Repository:

   git clone https://github.com/your-username/AI-Othello.git
   cd AI-Othello

2. Launch Jupyter Notebook:

   Open a terminal or command prompt and run:

   jupyter notebook

3. Open the Notebook:

   In the Jupyter interface, navigate to the directory where you cloned the repository and open the AI-Othello.ipynb file.

4. Play the Game:

   • Run the cells in the notebook to initialize the game.
   • The game will display the board, and you can make your moves by selecting the appropriate cells.
   • The AI will respond with its move after you make yours.

• Othello is played on an 8x8 board with two players: one with black discs and the other with white discs.
• The goal is to have the majority of your color discs on the board at the end of the game.
• Players take turns placing a disc on the board. A move must outflank one or more of the opponent's discs, and the outflanked discs are flipped to the player's color.
• The game ends when neither player can make a valid move.

• AI Difficulty: The AI's difficulty can be adjusted by changing the depth of the Minimax algorithm. Increase the depth for a more challenging opponent or decrease it for an easier game.

• AI-Othello.ipynb: The Jupyter Notebook containing the game code and interface.
• othello.py: (Optional) A Python script that encapsulates the game logic, used within the notebook.

• Implement additional AI strategies, such as Monte Carlo Tree Search.
• Add a graphical user interface (GUI) for a more user-friendly experience.
• Allow multiplayer mode for two human players.

This project is licensed under the MIT License. Feel free to use, modify, and distribute it as you wish.

Contributions are welcome! If you'd like to contribute to the project, feel free to submit a pull request or open an issue to discuss improvements.

• Inspired by classic Othello board games.
• AI implemented using the Minimax algorithm with inspiration from various online resources and AI textbooks.