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Chess Bot Projects Repository

Overview

This repository hosts a collection of four distinct chess bot projects, each exploring different approaches to chess AI development, ranging from handcrafted algorithms to advanced machine learning and beyond. The addition of the AI-ZeroChessBot-C++ project marks a significant milestone in our exploration, representing the most developed and sophisticated chess engine in our collection. It is a direct port of the AI-ZeroChessBot to C++, further developed to leverage the performance benefits of the language. From foundational frameworks to cutting-edge techniques, these projects aim to cover a comprehensive spectrum of AI strategies in the domain of chess. Each project is contained within its own subfolder, allowing for focused development and exploration.

Projects

0. Framework (Subfolder: Framework)

Provides the basic infrastructure for evaluating and playing chess games, serving as the foundation for the other projects. Includes essential classes such as ChessBot, GameManager, HumanPlayer, and Tournament.

1. HandcraftedChessBot (Subfolder: HandcraftedChessBot)

Focuses on traditional chess bot design principles, employing handcrafted evaluation functions and optimization techniques without machine learning.

Key Features:

  • Alpha-beta pruning and iterative deepening.
  • Handcrafted evaluation functions focusing on material count, piece-square tables, and pawn structure.

2. NeuralNetChessBot (Subfolder: NeuralNetChessBot)

Explores the integration of a neural network-based evaluator within a chess bot framework, aiming to assess chess positions dynamically through machine learning.

Key Features:

  • Neural network for position evaluation.
  • Training of the neural network with chess game datasets.

3. AI-ZeroChessBot (Subfolder: AI-ZeroChessBot)

Inspired by AlphaZero, this project combines deep neural networks with Monte Carlo Tree Search (MCTS) for move selection and position evaluation, learning from self-play.

Key Features:

  • Deep neural network with policy and value heads.
  • MCTS for strategic move selection.
  • Self-play for continuous learning.

4. AI-ZeroChessBot-C++ (Subfolder: AI-ZeroChessBot-C++)

A significant evolution of the AI-ZeroChessBot, ported to C++ and further developed to harness the language's performance capabilities. This project represents the pinnacle of our chess engine development, emphasizing efficiency, advanced strategies, and self-improvement through deep learning and MCTS.

Key Features:

  • Ported to C++ for enhanced performance and efficiency.
  • Advanced integration of deep learning and MCTS for superior strategic depth.
  • Focus on self-improvement through extensive self-play and continuous learning.

Repository Structure

ChessBot/
│
├── Framework/
│   └── README.md
│
├── HandcraftedChessBot/
│   └── README.md
│
├── NeuralNetChessBot/
│   └── README.md
│
├── AI-ZeroChessBot/
│   └── README.md
│
└── AI-ZeroChessBot-C++/
    └── README.md

Getting Started

To get started with any of the projects:

  1. Clone this repository to your local machine.
  2. Navigate to the project subfolder of interest (HandcraftedChessBot, NeuralNetChessBot, AI-ZeroChessBot, or AI-ZeroChessBot-C++).
  3. Follow the instructions in the project-specific README.md for setup and running the bot.
  4. To explore the basic chess bot framework, refer to the Framework subfolder and try it out via python -m Framework.