ainaherimam/mcts-fanorona

An implementation of the Monte Carlo Tree Search (MCTS) algorithm for the malagasy board game: Fanorona # Fanorona with MCTS A project that implements the Monte Carlo Tree Search (MCTS) algorithm for the traditional board game of Fanorona. --- ## 📖 About Fanorona Fanorona is a centuries-old strategy board game originating from Madagascar. It is played on a 9x5 grid (fanorona 9) or a 5x5 grid (fanorona 5) and challenges players to capture their opponent's pieces using a variety of strategic moves. The game is renowned for its depth and complexity, making it an excellent candidate for AI research. --- ## 🎯 Project - Implement a simple interface for - Implement the **Monte Carlo Tree Search (MCTS)** algorithm to play Fanorona. - Develop an algorithm capable of making intelligent, adaptive decisions. --- ## 🚀 Features - **Fanorona Game Logic**: The game board is represented programmatically, supporting all valid moves and captures. - **MCTS Algorithm**: To calculate optimal moves. - **Interactive Gameplay**: Play against the AI --- ## 🛠️ Getting Started ### Prerequisites Ensure you have the following installed: - Python 3 ### Installation 1. Clone the repository: ```bash git clone github.com cd mcts-fanorona ``` 2. Run the game ```bash python main.py ``` --- ## 🛠️ To do - simulate AI vs. AI matches - Optimize the code for more simulations --- ## 📂 Repository Structure ``` mcts-fanorona/ ├── mcts.py # MCTS implementation ├── fanorona.py # Fanorona implementation └── README.md # Project documentation ``` --- ## 🌟 Acknowledgments - Inspired by the board game Fanorona) - Thanks to maksimKorzh for the help on the MCTS part. Enjoy playing and exploring the strategies of Fanorona!