Initial Release v1.0.0

This is the initial release of the ChessSL supervised learning chess engine with Monte Carlo Tree Search (MCTS).

Implemented features

• ResNetCBAM model
• BatchMCTS algorithm
• A minimal implementation for the Universal Chess Interface (UCI) protocol

As of 23/Nov/2024, the engine has achieved a rating of 2154 in bullet mode and 2113 in blitz mode on Lichess, which is better than 90.3% and 94.7% players.

Issues

• Our neural network is very weak, compared to the Lc0's network.
• Our batch MCTS algorithm can be improved
• Lacking an "arena" mechanism to compare two version of the engine
• The UCI protocol is only good enough for the lichess API

This is probably the final release as I have invested too much time into this project. Nevertheless, I had a lot of fun and the final result is satisfactory.