twitchchess
A toy implementation of neural network normal chess written while livestreaming.
Can beat me at bullet, maybe rated 1200-1400. Search is 3-ply full with a 5-ply beam(x10).
Nice TODO
- Value function in play.py/ClassicValuator, plenty of room for improvement.
- Add Quiescence search to play decent endgame
- Is there a bug which allows draws to happen?
Stream
https://www.twitch.tv/tomcr00s3
Usage
pip3 install python-chess torch torchvision numpy flask
# then...
./play.py # runs webserver on localhost:5000
Or with pypy (for max speed)
pip_pypy install python-chess flask
pypy ./play.py
# web browse to localhost:5000
TODOs
- Roll out search beyond 1-ply
- Make trainer multi GPU
- Train on more data
- Add RL self play learning support
Implementation
twitchchess 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/