Mark Boon wrote: >Let me therefore change the discussion a bit to see if this will make >things more clear. Consider a chess-playing program with an >unorthodox search method. When playing a human after while it >announces check-mate in thirty-four moves. Yet the human can clearly >see it's check-mate in four. Ah, one could say, but the computer is >100% confident winning either way so it doesn't care which one it >chooses. It doesn't matter whether a human thinks mate in four is >more beautiful.
>Now it so happens that with chess we're pretty confident that when a >chess-program announces check-mate that it is in fact correct. But >what if there could be a sliver of doubt? Maybe the program has no >doubt, but the programmer might. Bugs happen. Wouldn't you say it's >better to choose the shorter mate sequence? Regardless of whether >humans may find it more beautiful? Any probabilistic algorithm should of course prefer a quick win to a tedious one, since there is less assumptions it has to make, the less likely it is that one of them is disastrously wrong. But wouldn't they actually take that into account in their win estimates? Anyway, turns to win is a completely different measure than score at end. But I found something that may interest you. Three researchers at a Paris university, Julien Kloetzer Hiroyuki Iida and Bruno Bouzy, implemented a UCT program for playing Amazons. They found that for that game, performance increased when the algorithm took into account winning margin in addition to win/loss. I wonder what that means. Perhaps "greedy" strategies work better in Amazons than in Go? The program lost big in the olympiad, though, against a more traditional program, so it might be premature to draw conclusions... Here's the research paper: www.math-info.univ-paris5.fr/~bouzy/publications/KIB-MCAmazons-CGW07.pdf _______________________________________________ computer-go mailing list [email protected] http://www.computer-go.org/mailman/listinfo/computer-go/
