Imagine that your score estimator has a better idea about the outcome of the game than the players themselves.
Then you can build a stronger computer player with the following algorithm: use the score estimator to pick the next move after evaluating all legal moves, by evaluating their after-move scores. If you use something like Tromp-Taylor (not sure what most people use nowadays) then you can score it less equivocally. Perhaps I was misunderstanding, but if not then this could be a somewhat serious problem. s On Sun, Dec 9, 2018, 6:17 PM cody2007 <cody2...@protonmail.com wrote: > >By the way, why only 40 moves? That seems like the wrong place to > economize, but maybe on 7x7 it's fine? > I haven't implemented any resign mechanism, so felt it was a reasonable > balance to at least see where the players roughly stand. Although, I think > I errored on too few turns. > > >A "scoring estimate" by definition should be weaker than the computer > players it's evaluating until there are no more captures possible. > Not sure I understand entirely. But would agree that the scoring I use is > probably a limitation here. > > ‐‐‐‐‐‐‐ Original Message ‐‐‐‐‐‐‐ > On Sunday, December 9, 2018 8:51 PM, uurtamo <uurt...@gmail.com> wrote: > > 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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