bargallosam

I’m working on a class for the game logic of the Go board. This will serve as the foundation of move validation and game state handling. I had to do a lot of research about the specific mechanics of the game with Ko and capture rules. It was surprisingly hard to implement every rule programmatically, and I think my current methods might be a little slow… I optimized some methods using caching and hashing, but I may have to look for other optimizations later if the model trains too slowly.

I’ve done some research on Reinforcement Learning and how I could code a Go model. So far, I’ve decided on using Python/flask as a backend, with Redis serving as the source of truth. I want anyone who goes to this site to see the same Go game being played, so I’ll need some sort of persistence. I’m gonna mess around with a basic PyTorch model for right now and see if I can get a basic game loop up and running first…