Bagh Chal is one of the many variants of the tiger hunting board games played locally in South East Asia. The strategic, two-player board game is played on a 5x5 grid.
Inspired by AlphaZero, the project tries to use state-of-the-art methods in the deep reinforcement learning paradigm to master the traditional Nepali board game of Bagh Chal through self-play. It uses a single deep residual convolutional neural network which takes in a multilayered binary board state and outputs both the game policy and value, along with Monte Carlo Tree Search.
Check out the accompanying blog where I write about my experience developing this self-learning AI agent: Mastering Bagh Chal with self-learning AI
- Tabula Rasa Learning
- Better training
- Pytorch version