CNN-based CHESS AI

Overview

CNN-based CHESS AI is an artificial intelligence project that utilizes Convolutional Neural Networks (CNNs) to play chess. The objective is to predict optimal chess moves using deep learning, learning from historical chess game data, and mapping board states to the most likely next moves.

Features

• Deep learning-based chess move prediction using CNNs.
• Converts board states (FEN notation) to neural network-compatible tensors.
• Modular approach for predicting chess moves.
• Includes scripts for training, evaluating, and move suggestion.
• Move suggestion available for any given chess position.

Installation

1. Clone the repository:

   git clone https://github.com/SAHILMPATIL/CNN-based-CHESS-AI.git
   cd CNN-based-CHESS-AI
   

2. Install dependencies:

   • Python 3.x required
   • Install the necessary libraries:

     pip install tensorflow keras python-chess numpy
     

Usage

Training the Models

• Use the training scripts inside the repository to train the CNN models using your dataset.

Predicting Moves

After training, you can use the trained model to predict the next move for a given chess board position.

Example usage in Python (requires your model and API):

Refer to the scripts and notebooks (predict.py, etc.) in the repository to match the actual function and usage patterns.

Project Structure

Requirements

• Python 3.6+
• TensorFlow
• Keras
• numpy
• python-chess

Install dependencies with:

How to Contribute

1. Fork this repository.
2. Create a new branch (git checkout -b feature-branch-name).
3. Add your changes.
4. Commit and push your branch.
5. Open a Pull Request explaining your changes.

License

This project is open-source; see the LICENSE file for details.

Contact

For questions or suggestions, please open an issue.

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This README provides a template and general instructions for the CNN-based CHESS AI project. Update specific paths, commands, and function calls as needed to match your actual codebase structure.