[Computer-go] Mcts and tactics

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


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.


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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