According this analysis, move 78 is not a "miracle" move ... http://card.weibo.com/article/h5/s#cid=23041853a2e03d0102w6rl&;
On Mon, Mar 14, 2016 at 4:08 AM, Martin Mueller <mmuel...@ualberta.ca> wrote: > On Mar 13, 2016, at 6:00 AM, computer-go-requ...@computer-go.org wrote: > > > So, what would be Lee's best effort to exploit this? Complicating > and playing hopefully-unexpected-tesuji moves? > > > Judging from this game, setting up multiple interrelated tactical fights, > such that no subset of them works, but all together they work to capture or > kill something. > > For tactical fights, I would expect the value network to be relatively > weaker than for quiet territorial positions. > So it comes down to solving the problem by search. > > Aja and me wrote a paper a few years back that showed that even on a 9x9 > board, having two safe but not entirely safe-in-playouts groups on the > board confuses most Go programs and can push the “bad news” over the search > horizon. Now imagine having 3, 4, 5 or more simultaneous tactics. The > combinatorics of searching through all of those by brute force are > enormous. But humans know exactly what they are looking for. > Martin > > Reference: > http://webdocs.cs.ualberta.ca/~mmueller/publications.html#2013 > > *S.-C. Huang* and M. Müller. Investigating the Limits of Monte Carlo Tree > Search Methods in Computer Go > <http://webdocs.cs.ualberta.ca/~mmueller/ps/2013/2013-CG-MCTS-Go-Limits.pdf>. > Computers and Games 2013, p. 39-48. > *Erratum > <http://webdocs.cs.ualberta.ca/~mmueller/ps/2013/2013-CG-MCTS-Go-Limits-erratum.txt>* > for > this paper - in test case 2 Black wins. > > > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go >
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