[Computer-go] Mastering the Game of Go with Deep Neural Networks and Tree Search

Hideki Kato hideki_katoh at ybb.ne.jp
Mon Feb 1 04:07:22 PST 2016

Olivier Teytaud: <CAMpyiGN-3nWxivfMv2uJiAyzVj7zLxt8T=eci+_r0UwCCRxqeQ at mail.gmail.com>: 
>If AlphaGo had lost at least one game, I'd understand how people can have
>an upper bound on its level, but with 5-0 (except for Blitz) it's hard to

No, the other five are not blitz games.  Quoting from the 
paper (pp. 28):
Time controls for formal games were 1 hour main time plus 3 
period of 30 seconds byoyomi.  Time controls for informal games 
were 3 periods of 30 seconds byoyomi.


>have an upper bound on his level. After all, AlphaGo might just have played
>well enough for crushing Fan Hui, and a weak move while the position is
>still in favor of AlphaGo is not really a weak move (at least in a
>game-theoretic point of view...).
>On Mon, Feb 1, 2016 at 12:12 PM, Petr Baudis <pasky at ucw.cz> wrote:
>>   Hi!
>> On Mon, Feb 01, 2016 at 09:19:56AM +0000, Darren Cook wrote:
>> > > someone cracked Go right before that started. Then I'd have plenty of
>> > > time to pick a new research topic." It looks like AlphaGo has
>> > > provided.
>> >
>> > It seems [1] the smart money might be on Lee Sedol:
>> >
>> > 1. Ke Jie (world champ) – limited strength
but still amazing
 Less than
>> > 5% chance against Lee Sedol now. But as it can go stronger, who knows
>> > its future

>> > 2. Mi Yuting (world champ) – appears to be a ‘chong-duan-shao-nian (kids
>> > on the path to pros)’, ~high-level amateur.
>> > 3, Li Jie (former national team player) – appears to be pro-level. one
>> > of the games is almost perfect (for AlphaGo)
>> >
>> >
>> > On the other hand, AlphaGo got its jump in level very quickly (*), so it
>> > is hard to know if they just got lucky (i.e. with ideas things working
>> > first time) or if there is still some significant tweaking possible in
>> > these 5 months of extra development (October 2015 to March 2016).
>>   AlphaGo's achievement is impressive, but I'll bet on Lee Sedol
>> any time if he gets some people to explain the weaknesses of computers
>> and does some serious research.
>>   AlphaGo didn't seem to solve the fundamental reading problems of
>> MCTS, just compensated with great intuition that can also remember
>> things like corner life&death shapes.  But if Lee Sedol gets the game to
>> a confusing fight with a long semeai or multiple unusual life&death
>> shapes, I'd say based on what I know on AlphaGo that it'll collapse just
>> as current programs would.  And, well, Lee Sedol is rather famous for
>> his fighting style.  :)
>>   Unless of course AlphaGo did achieve yet another fundamental
>> breakthrough since October, but I suspect it'll be a long process yet.
>> For the same reason, I think strong players that'd play against AlphaGo
>> would "learn to beat it" just as you see with weaker players+bots on
>> KGS.
>>   I wonder how AlphaGo would react to an unexpected deviation from a
>> joseki that involves a corner semeai.
>> > [1]: Comment by xli199 at
>> >
>> http://gooften.net/2016/01/28/the-future-is-here-a-professional-level-go-ai/
>> >
>> > [2]: When did DeepMind start working on go? I suspect it might only
>> > after have been after the video games project started to wound down,
>> > which would've Feb 2015? If so, that is only 6-8 months (albeit with a
>> > fairly large team).
>>   Remember the two first authors of the paper:
>>   * David Silver - his most cited paper is "Combining online and offline
>>     knowledge in UCT", the 2007 paper that introduced RAVE
>>   * Aja Huang - the author of Erica, among many other things
>>   So this isn't a blue sky research at all, and I think they had Go in
>> crosshairs for most of the company's existence.  I don't know the
>> details of how DeepMind operates, but I'd imagine the company works
>> on multiple things at once. :-)
>> --
>>                                 Petr Baudis
>>         If you have good ideas, good data and fast computers,
>>         you can do almost anything. -- Geoffrey Hinton
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>Olivier Teytaud, olivier.teytaud at inria.fr, TAO, LRI, UMR 8623(CNRS - Univ.
>bat 490 Univ. Paris-Sud F-91405 Orsay Cedex France
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Hideki Kato <mailto:hideki_katoh at ybb.ne.jp>

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