[Computer-go] Mastering the Game of Go with Deep Neural Networks and Tree Search
teytaud at lri.fr
Mon Feb 1 03:24:21 PST 2016
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
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:
> 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  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
> I wonder how AlphaGo would react to an unexpected deviation from a
> joseki that involves a corner semeai.
> > : Comment by xli199 at
> > : 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
> Computer-go mailing list
> Computer-go at computer-go.org
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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