Not in this weak state of the learned net. I measure with a net trained from 4d+ kgs games right now on CGOS (NG-learn-ref).
This should be the line, which could be beaten by Zero after enough learning. If I manage to beat this version (I check every learning cycle 10 games against this version) than I will probably also measure the strength of this, but I think this will take some weeks:) Am 06.11.2017 um 17:05 schrieb uurtamo .: > Detlef, > > I misunderstand your last sentence. Do you mean that eventually you'll put > a subset of functioning nets on CGOS to measure how quickly their strength > is improving? > > s. > > On Nov 6, 2017 4:54 PM, "Detlef Schmicker" <d...@physik.de> wrote: > >> I thought it might be fun to have some games in early stage of learning >> from nearly Zero knowledge. >> >> I did not turn off the (relatively weak) playouts and mix them with 30% >> into the result from the value network. I started at an initial random >> neural net (small one, about 4ms on GTX970) and use a relatively wide >> search for MC (much much wider, than I do for good playing strength, >> unpruning about 5-6 moves) and 100 playouts expanding every 3 playouts, >> thus 33 network evaluations per move. >> >> Additionally I add Gaussian random numbers with a standard derivation of >> 0.02 to the policy network. >> >> With this setup I play 1000 games and do an reinforcement learning cycle >> with them. One cycle takes me about 5 hours. >> >> The first 2 days I did not archive games, than I noticed it might be fun >> having games from the training history: now I always archive one game >> per cycle. >> >> >> Here are some games ... >> >> >> http://physik.de/games_during_learning/ >> >> >> I will probably add some more games, if I have them and will try to >> measure, how strong the bot is with exactly this (weak broad search ) >> configuration but a pretrained net from 4d+ kgs games on CGOS... >> >> >> Detlef >> _______________________________________________ >> Computer-go mailing list >> Computer-go@computer-go.org >> http://computer-go.org/mailman/listinfo/computer-go > > > > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go > _______________________________________________ Computer-go mailing list Computer-go@computer-go.org http://computer-go.org/mailman/listinfo/computer-go