[Computer-go] Mcts and tactics

Dan dshawul at gmail.com
Wed Dec 20 06:34:53 PST 2017


Thanks!

It would be interesting to see the performance of the policy network alone
in chess and shogi too.

There is no such plot in the arxiv paper.

Honestly, I don't expect it to be that good since engines without a
lookahead search never performed

that well in these domains -- unlike Go which has GnuGo, a very strong
player before the MC era.

Daniel

On Tue, Dec 19, 2017 at 11:57 PM, patrick.bardou via Computer-go <
computer-go at computer-go.org> wrote:

> Hi Daniel,
>
> AGZ paper: greedy player based on policy network (= zero look-ahead) has
> an estimated ELO of 3000 ~ Fan Hui 2p.
>
> Professional player level with Zero look-ahead. For me, it is the other
> striking aspect of 'Zero' ! ;-)
>
> IMO, this implies that the NN has indeed captured lots of tactics. Even if
> tactics may not be as important in go as in chess, it still matters a lot,
> not just in capturing races. It is often at the foundation of the value of
> a position (e.g.: life & death status of a group; "value of this position
> is X because there exist sequences such that this black group can either
> live or link").
>
> Hard to imagine 2p level without a great deal of tactics, just strong
> positional judgment. Practicaly, for MCTS guided by policy and value
> networks, this means the policy networks has to assign good prior to
> tactical moves.
>
> BR,
> Patrick
>
>
>
> -------- Message d'origine --------
> De : computer-go-request at computer-go.org
> Date : 20/12/2017 01:57 (GMT+01:00)
> À : computer-go at computer-go.org
> Objet : Computer-go Digest, Vol 95, Issue 24
>
>
> Message: 1
> Date: Tue, 19 Dec 2017 16:26:00 -0700
> From: Dan <dshawul at gmail.com>
> To: computer-go at computer-go.org
> Subject: [Computer-go] mcts and tactics
> Message-ID:
> <CAN8pvoThwxz2cSMLkFZJTL_hYvaS6tchzE3YgJQoZV6Vic+u-A at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Hello all,
>
> It is known that MCTS's week point is tactics. How is AlphaZero able to
> resolve Go tactics such as ladders efficiently? If I recall correctly many
> people were asking the same question during the Lee Sedo match -- and it
> seemed it didn't have any problem with ladders and such.
>
> In chess and shogi, there is lots of tactics and plain MCTS as used in
> AlphaZero shouldn't perform well (one would expect), but apparently
> AlphaZero didn't seem to have a problem in that regard against stockfish.
> First of all, I think that AlphaZero is resolving tactics by growing its
> MCTS tree very rapidly (expand after each visit) -- some people thought
> initially that NN may have some tactics in it but I don't believe it can do
> better than a quiescence_search. Tactics requires precise calculations with
> moves that maynot make sense (sacrfice) -- apparently AlphaZero's
> positional understanding led it to be superior in this regard as well.
>
> My simple MCTS chess engine (single thread) is now better in tactics than
> it used to be (after removing the rollouts), but it is still far far from
> the tactical ability of alpha-beta engines with LMR+nullmove. What do you
> think is AlphaZero's tactical strength coming from ? I am guessing parallel
> MCTS with larger exploration coefficient for each thread -- this should
> explore  enough not so good moves closer to the root not to miss sshallow
> tactics.
>
> I just wanted to know the opinions of the MCTS experts.
>
>
>
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