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 < [email protected]> 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 : [email protected] > Date : 20/12/2017 01:57 (GMT+01:00) > À : [email protected] > Objet : Computer-go Digest, Vol 95, Issue 24 > > > Message: 1 > Date: Tue, 19 Dec 2017 16:26:00 -0700 > From: Dan <[email protected]> > To: [email protected] > Subject: [Computer-go] mcts and tactics > Message-ID: > <can8pvothwxz2csmlkfzjtl_hyvas6tchze3ygjqozv6vic+...@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. > > > > _______________________________________________ > Computer-go mailing list > [email protected] > http://computer-go.org/mailman/listinfo/computer-go >
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