/Chess-ML

Machine Learning Chess Master

Primary LanguagePythonMIT LicenseMIT

twitchchess

A toy implementation of neural network chess.

Usage

 # install pytorch and flask and probably more stuff
 # TODO: document more stuff
 # then...
 ./play.py   # runs webserver on localhost:5000

TODOs

  • Roll out search beyond 1-ply
  • Make trainer multi GPU
  • Train on more data
  • Add RL self play learning support

Implementation

Chess is a simple 1 look ahead neural network value function. The trained net is in nets/value.pth. It takes in a serialized board and outputs a range from -1 to 1. -1 means black is win, 1 means white is win.

Serialization

We serialize the board into a 8x8x5 bitvector. See state.py for how.

Training Set

The value function was trained on 5M board positions from http://www.kingbase-chess.net/