Google beats Fan Hui, 2 dan pro, 5-0 (19x19, no handicap)!
Congratulations! I am proud of my student Aja. They'll play Lee Sedol in
March.
It's a pity they don't participate in the UEC Cup.
I read the paper. The most original idea is in learning a value network.
It seems to be extremely efficient.
Rémi
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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 - surely the NDAs no longer apply, and you can now tell us
all the details?
Darren
P.S. Curiously the BBC ran an article today on how Facebook is getting
close to top pro level too: http://www.bbc.co.uk/news/technology-35419141
Rémi, Is the paper of which you speak available?
Many thanks,
Erik S. Steinmetz
er...@steinmetz.org
(612) 789-6940
(612) 978-4342 cell
Interesting times we live in!
-John
http://googleresearch.blogspot.be/2016/01/alphago-mastering-ancient-game-of-go.html
"The match was played behind closed doors between October 5-9 last year."
They already achieved this a while ago. The Google announcement looks
like a direct response to the press Facebook was getting.
--
GCP
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
--
-- Yoshiki
On 01/27/2016 06:58 PM, Darren Cook wrote:
> Is it available online anywhere, or only in Nature?
_______________________________________________
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...@free.fr>:
--
Hideki Kato <mailto:hideki...@ybb.ne.jp>
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 still unclear to me.
Thanks,
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 online bookshop), Havannah and Breakthrough. Richard found that in many
applications a truncation level of 4 moves seem to work quite well.
There is a paper by him on this topic in the proceedings of the conference
Advances in Computer Games 2015 (in Leiden , NL), published by Springer
Lecture Notes in Computer Science (LNCS).
A very early application of truncated rollouts was applied by Brian
Sheppard in his bot for Scrabble (MAVEN).
Ingo.
https://acg2015.files.wordpress.com/2015/07/lorentz.pdf
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 evaluation
exists, see e.g. my two books Positional Judgement.
--
robert jasiek
Thanks. Has anyone (strong) made commented versions yet? I played
through the first game, but it just looks like a game between two
players much stronger than me :-)
(Ingo, are you analyzing them with e.g. CrazyStone? Is there a
particular point where it adjusts who it thinks is winning?)
Darren
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
> 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 <dar...@dcook.org
> <mailto:dar...@dcook.org>>:
>
> > 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 just looks like a game between two
> players much stronger than me :-)
>
> (Ingo, are you analyzing them with e.g. CrazyStone? Is there a
> particular point where it adjusts who it thinks is winning?)
>
> Darren
>
> _______________________________________________
> Computer-go mailing list
> Compu...@computer-go.org <mailto:Compu...@computer-go.org>
> http://computer-go.org/mailman/listinfo/computer-go
Now Fan Hui either blundered badly afterwards, or more promising, it
could be hard for humans to evaluate AlphaGo's play at this point
because they undervalue some it its choices. Which of course would be
similar to how some moves by the first world-beating chess AIs have
been treated by human experts.
AlphaGo might be even more of a wild card than it seems.
Also, on another note, that Google set up those Sedol games makes me
assume that they are convinced of actually succeeding. The Fan Hui
matches have been months ago, and AlphaGo will have spent that time
learning, and when the matches come around they will probably throw A
LOT of processing power at Sedol. I don't think they would try for so
much public reach to then fail and be associated with failure and
hybris.
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.
Thanks for the pointer.
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 as particularly good, e.g.
108, which is also an empty triangle: obviously AlphaGo isn't being held
back by any "good shape" heuristics ;-)
I hope he comments the other four games!
Darren
--
Darren Cook, Software Researcher/Developer
My new book: Data Push Apps with HTML5 SSE
Published by O'Reilly: (ask me for a discount code!)
http://shop.oreilly.com/product/0636920030928.do
Also on Amazon and at all good booksellers!
There have been some efforts at whole-board evaluation in Go. Maybe NeuroGo was the earliest really cool demonstration. But I never saw anything that gave me confidence that the approach could work when embedded in an MCTS framework. I am blown away.
the following is confidential, only for you.
I do not know, how the situation with your go project is.
But please let me know if I can help you in some way or another
to convince your boss that further work on computer-go makes
sense for facebook.
Best regards, Ingo.
Strictly confidential, I dare say!