Re: [Computer-go] Game Over

[mailto:computer-go-boun...@computer-go.org] On Behalf Of "Ingo Althöfer" Sent: Thursday, January 28, 2016 1:00 AM To: computer-go@computer-go.org Subject: Re: [Computer-go] Game Over Hello Anders, thanks for the summary on the smartgo site. > ... the truncated rollouts mentioned in the pa

Re: [Computer-go] Game Over

On 28.01.2016 04:57, Anders Kierulf wrote: Please let me know if I misinterpreted anything. You write "Position evaluation has not worked well for Go in the past" but I think you should write "...Computer Go..." because applicable, reasonably accurate theory for human players' positional

Re: [Computer-go] Game Over

I find it interesting that right until he ends his review, Antti only praises White's moves, which are the human ones. When he stops, he even considers a win by White as basically inevitable. Now Fan Hui either blundered badly afterwards, or more promising, it could be hard for humans to evaluate

Re: [Computer-go] Game Over

That would make my writing nonsense of course. :) Thanks for the pointer. On Thu, Jan 28, 2016 at 12:26 PM, Xavier Combelle wrote: > > > 2016-01-28 12:23 GMT+01:00 Michael Markefka : >> >> I find it interesting that right until he ends his

Re: [Computer-go] Game Over

Hi Xavier, Really nice comments by Antti Törmänen, to the point and very clear explanation. Thanks for the pointer. best regards, Jan van der Steen On 28-01-16 11:45, Xavier Combelle wrote: here a comment by Antti Törmänen

Re: [Computer-go] Game Over

here a comment by Antti Törmänen http://gooften.net/2016/01/28/the-future-is-here-a-professional-level-go-ai/ 2016-01-28 11:19 GMT+01:00 Darren Cook : > > If you want to view them in the browser, I've also put them on my blog: > > >

Re: [Computer-go] Game Over

> If you want to view them in the browser, I've also put them on my blog: > http://www.furidamu.org/blog/2016/01/26/mastering-the-game-of-go-with-deep-neural-networks-and-tree-search/ > (scroll down) Thanks. Has anyone (strong) made commented versions yet? I played through the first game, but it

Re: [Computer-go] Game Over

> here a comment by Antti Törmänen > http://gooften.net/2016/01/28/the-future-is-here-a-professional-level-go-ai/ Thanks, exactly what I was looking for. He points out black 85 and 95 might be mistakes, but didn't point out any dubious white (computer) moves. He picks out a couple of white moves

Re: [Computer-go] Game Over

To the authors: Did the deep-NN architecture learn ladders on its own, or was any extra ladder-evaluation code added to the playout module? ___ Computer-go mailing list Computer-go@computer-go.org http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] Game Over

It's in the paper: "ladder capture" and "ladder escape" are features that are fed as inputs into the CNN. Álvaro. On Wed, Jan 27, 2016 at 6:03 PM, Ryan Grant wrote: > To the authors: Did the deep-NN architecture learn ladders on its own, > or was any extra

Re: [Computer-go] Game Over

Congratulations to Aja & DeepMind team! Amazing results :) Yuandong Tian Research Scientist, Facebook Artificial Intelligence Research (FAIR) Website: https://research.facebook.com/researchers/1517678171821436/yuandong-tian/

Re: [Computer-go] Game Over

Congrats to the AlphaGo team — a tremendous accomplishment! I've been reading the paper and have written up a summary of what they did: https://smartgo.com/blog/google-alphago.html Please let me know if I misinterpreted anything. Also, the truncated rollouts mentioned in the paper are

Re: [Computer-go] Game Over

Congratulations to Aja $ DeepMind to that great result! I am curious to see AlphaGo having to play a tough narrow endgame. In the first of the 5 games it could affort not to play totally optimal in the end and in the next 4 games Fan resigned. End games require again other, more math like

Re: [Computer-go] Game Over

Hello Anders, thanks for the summary on the smartgo site. > ... the truncated rollouts mentioned in the paper are still unclear to me. The greatest expert on these rollouts might be Richard Lorentz. He applied them successfully to his bots in the games Amazons (not to be mixed up with the

Re: [Computer-go] Game Over

http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html well done Aja :) On Wed, Jan 27, 2016 at 5:59 PM, Erik S. Steinmetz wrote: > This seems quite amazing. Congratulations to the Google DeepMind team and > AlphaGo! > > Rémi, Is the paper of which you speak

Re: [Computer-go] Game Over

I foresee a future where we watch Google vs Facebook matches with human professionals providing commentary on their superiors :-) Interesting times we live in! -John ___ Computer-go mailing list Computer-go@computer-go.org

Re: [Computer-go] Game Over

for those looking for sgfs: http://deepmind.com/alpha-go.html 2016-01-27 19:25 GMT+01:00 Julian Schrittwieser : > Actually the paper has been in the works for quite a while and was already > set to be released today for some weeks. > It seems a journalist reached out

Re: [Computer-go] Game Over

Distributed AlphaGo is stronger than CrazyStone by +1200 Elo?! AlphaGo: Mastering the ancient game of Go with Machine Learning http://googleresearch.blogspot.jp/2016/01/alphago-mastering-ancient-game-of-go.html Hiroshi Yamashita - Original Message - From: "Rémi Coulom"

Re: [Computer-go] Game Over

If you want to view them in the browser, I've also put them on my blog: http://www.furidamu.org/blog/2016/01/26/mastering-the-game-of-go-with-deep-neural-networks-and-tree-search/ (scroll down) On Wed, Jan 27, 2016 at 6:28 PM, Marc Landgraf wrote: > for those looking for

Re: [Computer-go] Game Over

Actually the paper has been in the works for quite a while and was already set to be released today for some weeks. It seems a journalist reached out to Facebook to comment a day ago. On Wed, Jan 27, 2016 at 6:19 PM, Gian-Carlo Pascutto wrote: > On 27/01/2016 18:58, Darren Cook

Re: [Computer-go] Game Over

> Google beats Fan Hui, 2 dan pro, 5-0 (19x19, no handicap)! > ... > I read the paper... Is it available online anywhere, or only in Nature? I just watched the video, which was very professionally done, but didn't come with the SGFs, information on time limits, number of CPUs, etc. Aja, David -

Re: [Computer-go] Game Over

Thank you for the game records! I really am just a by stander and kibizer and a weak player, but isn't the style of Fan Hui going too low positions, keep making clusters, and do a local fight at a time? On Wed, Jan 27, 2016 at 10:29 AM, Julian Schrittwieser wrote: > If

Re: [Computer-go] Game Over

Congratulation! Really an excellent job, David and Aja! I imagined once but didn't think such value networks can be trained in practice, what a suprising machine power of the cloud! Hideki Remi Coulom: <56a919e2.9030...@free.fr>:

Re: [Computer-go] Game Over

https://storage.googleapis.com/deepmind-data/assets/papers/deepmind-mastering-go.pdf On 01/27/2016 06:58 PM, Darren Cook wrote: Is it available online anywhere, or only in Nature? ___ Computer-go mailing list Computer-go@computer-go.org