A "scoring estimate" by definition should be weaker than the computer players it's evaluating until there are no more captures possible.
Yes? s. On Sun, Dec 9, 2018, 5:49 PM uurtamo <uurt...@gmail.com wrote: > By the way, why only 40 moves? That seems like the wrong place to > economize, but maybe on 7x7 it's fine? > > s. > > On Sun, Dec 9, 2018, 5:23 PM cody2007 via Computer-go < > computer-go@computer-go.org wrote: > >> Thanks for your comments. >> >> >looks you made it work on a 7x7 19x19 would probably give better result >> especially against yourself if you are a complete novice >> I'd expect that'd make me win even more against the algorithm since it >> would explore a far smaller amount of the search space, right? >> Certainly something I'd be interested in testing though--I just would >> expect it'd take many months more months of training however, but would be >> interesting to see how much performance falls apart, if at all. >> >> >for not cheating against gnugo, use --play-out-aftermath of gnugo >> parameter >> Yep, I evaluate with that parameter. The problem is more that I only play >> 20 turns per player per game. And the network seems to like placing stones >> in terrotories "owned" by the other player. My scoring system then no >> longer counts that area as owned by the player. Probably playing more turns >> out and/or using a more sophisticated scoring system would fix this. >> >> >If I don't mistake a competitive ai would need a lot more training such >> what does leela zero https://github.com/gcp/leela-zero >> Yeah, I agree more training is probably the key here. I'll take a look at >> leela-zero. >> >> ‐‐‐‐‐‐‐ Original Message ‐‐‐‐‐‐‐ >> On Sunday, December 9, 2018 7:41 PM, Xavier Combelle < >> xavier.combe...@gmail.com> wrote: >> >> looks you made it work on a 7x7 19x19 would probably give better result >> especially against yourself if you are a complete novice >> >> for not cheating against gnugo, use --play-out-aftermath of gnugo >> parameter >> >> If I don't mistake a competitive ai would need a lot more training such >> what does leela zero https://github.com/gcp/leela-zero >> Le 10/12/2018 à 01:25, cody2007 via Computer-go a écrit : >> >> Hi all, >> >> I've posted an implementation of the AlphaZero algorithm and brief >> tutorial. The code runs on a single GPU. While performance is not that >> great, I suspect its mostly been limited by hardware limitations (my >> training and evaluation has been on a single Titan X). The network can beat >> GNU go about 50% of the time, although it "abuses" the scoring a little >> bit--which I talk a little more about in the article: >> >> >> https://medium.com/@cody2007.2/alphazero-implementation-and-tutorial-f4324d65fdfc >> >> -Cody >> >> _______________________________________________ >> Computer-go mailing >> listComputer-go@computer-go.orghttp://computer-go.org/mailman/listinfo/computer-go >> >> >> _______________________________________________ >> Computer-go mailing list >> Computer-go@computer-go.org >> http://computer-go.org/mailman/listinfo/computer-go > >
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