> There is something that the latest Monte Carlo programs have in common > with the best chess programs - and seems to be the right way to > structure a game tree search. Your selectivity should be > progressive. In order to do this correctly you must re-visit nodes > many times. Chess programs do it iteratively and Monte Carlo UCT type > programs do it "best first" fashion. So the decision to prune any given > move is a decision that is considered many times in the course of a > search - each time taking advantage of additional information. >
I think Monte-Carlo is more attempting solve a different issue altogether. Sure it is a search tree buyt main problem is the evaluation function. Currently we do not know any good way to evaluate the situation on go board until the game is at very late stages. And I think - not that I could support this with any testing - that most of the current evaluation function would not play better if they had deeper global search and actually may play worse with wider global search. Relatively speaking chess eval of adding piece values together and doing nothing else is far closer to optimal evaluation function that what is currently available in Go. Also there is not much published information evaluation functions in Go. Obviously a go programming is a business and giving out such information does not make sense. Best publicly available thingy is GnuGo and it does not even have one. Any simplistic Go-veal would probably result in very bad choices in early stages of game - like playing on second row without proper reason. So selective search is part of eval. And this shortcoming is pretty obvious in MC programs. when they play on full sized board they make extremely funny moves and so good result against humans only in ultra-blitz conditions - humans scale better I guess. Petri -- Petri Pitkänen e-mail: [EMAIL PROTECTED] Phone: +358 50 486 0292 _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
