Hello, I wanted to include this in my experimentation for augmenting a chess engine. I have prepared some datasets that represent each successive board state of 64 nodes (1 node for every space on the board) and along with it I have added edges with connecting nodes representing legal moves. I also have the stockfish evaluation of the board (so a positive/negative float representing who is winning based off of some specific heuristics that stockfish uses.) I want to first see if I can train a graph network to predict this board evaluation without any custom heuristics. Any chance you can point me in the right direction? I am familiar with pytorch lightning so was hoping I could just import your mode. The data I have prepared is arranged using networkx graph library by the way.
Thanks!
Hello, I wanted to include this in my experimentation for augmenting a chess engine. I have prepared some datasets that represent each successive board state of 64 nodes (1 node for every space on the board) and along with it I have added edges with connecting nodes representing legal moves. I also have the stockfish evaluation of the board (so a positive/negative float representing who is winning based off of some specific heuristics that stockfish uses.) I want to first see if I can train a graph network to predict this board evaluation without any custom heuristics. Any chance you can point me in the right direction? I am familiar with pytorch lightning so was hoping I could just import your mode. The data I have prepared is arranged using networkx graph library by the way.
Thanks!