That's not the point, Petri. 9x9 has almost no "silent"
or "static" positons which value networks superb humans.
On 9x9 boards, Kos, especially double Kos and two step Kos
are important but MCTS still works worse for them, for
examples. Human professionals are much better at life&death
and complex local fights which dominate small board games
because they can read deterministically and deeper than
current MCTS bots in standard time settings (not blitz).
Also it's well known that MCTS is not good at finding narrow
and deep paths to win due to "averaging". Ohashi 6p said
that he couldn't lose against statiscal algorithms after the
event in 2012.
>elo-range in 9x9 smaller than 19x19. One just cannot be hugelyl better than
>the other is such limitted game
>2018-02-23 21:15 GMT+02:00 Hiroshi Yamashita <y...@bd.mbn.or.jp>:
>> Top 19x19 program reaches 4200 BayesElo on CGOS. But 3100 in 9x9.
>> Maybe it is because people don't have much interest in 9x9.
>> But it seems value network does not work well in 9x9.
>> Weights_33_400 is maybe made by selfplay network. But it is 2946 in 9x9.
>> Weights_31_3200 is 4069 in 19x19 though.
>> In year 2012, Zen played 6 games against 3 Japanese Pros, and lost by 0-6.
>> And it seems Zen's 9x9 strength does not change big even now.
>> I feel there is still enough chance that human can beat best program in
>> Hiroshi Yamashita
>> Computer-go mailing list
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