Re: [Computer-go] Training an AlphaGo Zero-like algorithm with limited hardware on 7x7 boards

2020-01-26 Thread Igor Polyakov
I would be surprised if my model ever lost to GNU Go on 9x9. It's a lot stronger than Fuego, which already stomps GNU Go. It would be a waste of time to test it vs. GNU Go or even MCTS bots. I only plan on running tests vs. current best models to see how it does against the state of the art 9x9

Re: [Computer-go] Training an AlphaGo Zero-like algorithm with limited hardware on 7x7 boards

2020-01-26 Thread cody2007 via Computer-go
Thanks again for your thoughts and experiences Rémi and Igor. I'm still puzzled by what is making training slower for me than Rémi (although I wouldn't be surprised if Igor's results were faster when matched for hardware, model size, strength etc-- see below). Certainly komi sounds like it

Re: [Computer-go] Training an AlphaGo Zero-like algorithm with limited hardware on 7x7 boards

2020-01-26 Thread Igor Polyakov
I trained using David Wu's code for a few months on 9x9 only and it's been superhuman after a few months. I'm not sure if anyone's interested, but I can release my network to the world. It's around the strength of KataGo, but only on 9x9. I could do a final test before releasing it into the wild

Re: [Computer-go] Training an AlphaGo Zero-like algorithm with limited hardware on 7x7 boards

2020-01-26 Thread Rémi Coulom
Yes, using komi would help a lot. Still, I feel that something else must be wrong, because winning 100% of the games as Black without komi should be very easy on 7x7. I have not written anything about what I did with Crazy Stone. But my experiments and ideas were really very similar to what David