Re: [Computer-go] UEC Cup
Hi! On Mon, Mar 16, 2015 at 09:47:43AM +0100, Petr Baudis wrote: > A few blurry photos I took: > > > http://pasky-jp.soup.io/post/556768169/UEC-Cup-2015-exhibition-game-was-between > > http://pasky-jp.soup.io/post/556769031/The-prize-winners-Right-of-Remi-is > http://pasky-jp.soup.io/post/556769152/All-qualified-participants ...and a few more: http://pasky-jp.soup.io/post/557117614/In-the-spotlight-Cho-Chikun-one-of http://pasky-jp.soup.io/post/557117838/In-the-spotlight-Remi-Coulom-exclaiming-how http://pasky-jp.soup.io/post/557118024/The-game-was-commented-by-Yoda-Norimoto On Mon, Mar 16, 2015 at 09:55:34AM +0100, Kahn Jonas wrote: > So you were there, but did not have pachi play? Indeed, I'm in Japan for a while now but as I didn't have time to work on Pachi since UEC2013, it didn't seem to make sense to enter again with an old version. In retrospect, maybe I should have entered... :-) Petr Baudis ___ Computer-go mailing list Computer-go@computer-go.org http://computer-go.org/mailman/listinfo/computer-go
Re: [Computer-go] UEC Cup
> > DolBaram won the 4-handicap game against Cho Chikun 9p! > > ..but unfortunately, CrazyStone lost the 3-handicap game against > Cho Chikun. It made a dubious choice in the opening, but my guess > is that more importantly, a corner semeai with approach liberty was > left in one corner throughout the game. > Unresolved important stuff. The (not so) secret weapon against bots. ___ Computer-go mailing list Computer-go@computer-go.org http://computer-go.org/mailman/listinfo/computer-go
Re: [Computer-go] Teaching Deep Convolutional Neural Networks to Play Go
Hi Oliver Reinforcement learning is different to unsupervised learning. We used reinforcement learning to train the Atari games. Also we published a more recent paper (www.nature.com/articles/nature14236) that applied the same network to 50 different Atari games (achieving human level in around half). Similar neural network architectures can indeed be applied to Go (indeed that was one of the motivations for our recent ICLR paper). However, training by reinforcement learning from self-play is perhaps more challenging than for Atari: our method (DQN) was applied to single-player Atari games, whereas in Go there is also an opponent. I could not guarantee that DQN will be stable in this setting. Cheers Dave On 16 March 2015 at 22:21, Oliver Lewis wrote: > Can you say anything about whether you think their approach to > unsupervised learning could be applied to networks similar to those you > trained? Any practical or theoretical constraints we should be aware of? > > > On Monday, 16 March 2015, Aja Huang wrote: > >> Hello Oliver, >> >> 2015-03-16 11:58 GMT+00:00 Oliver Lewis : >>> >>> It's impressive that the same network learned to play seven games with >>> just a win/lose signal. It's also interesting that both these teams are in >>> different parts of Google. I assume they are aware of each other's work, >>> but maybe Aja can confirm. >>> >> >> The authors are my colleagues at Google DeepMind as on the paper they >> list DeepMind as their affiliation. Yes we are aware of each other's >> work. >> >> Aja >> >> > ___ > 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
Re: [Computer-go] UEC Cup
On Tue, Mar 17, 2015 at 07:00:02AM +0100, Petr Baudis wrote: > On Mon, Mar 16, 2015 at 06:37:14PM +0900, Rémi Coulom wrote: > > Tomorrow, the handicap will be 4 stones for DolBaram, and 3 stones for > > Crazy Stone. > > DolBaram won the 4-handicap game against Cho Chikun 9p! ..but unfortunately, CrazyStone lost the 3-handicap game against Cho Chikun. It made a dubious choice in the opening, but my guess is that more importantly, a corner semeai with approach liberty was left in one corner throughout the game. Petr Baudis ___ Computer-go mailing list Computer-go@computer-go.org http://computer-go.org/mailman/listinfo/computer-go
