On Thu, 2007-12-06 at 14:21 -0500, Don Dailey wrote: > > However, the estimated probability of winning may be way off. It is > > well known that Mogo, and perhaps some other programs, fail to > > recognize common nakade placements, which leads to fundamental > > estimation errors. An algorithm with more of a "fighting spirit" > > would defend against nakade, and attack enemy groups; perhaps making > > up for the loss of one group by the capture of another. > > > > Any algorithm which drives the win toward 0.5 is always going to be > > brittle; > It doesn't "drive" the win towards 0.5. It doesn't view them as any > differently. However, they will prefer a bigger win if there is any > room for error. Usually a bigger win is a more likely win - it's > only in the cases where it isn't that Monte Carlo program do not care. > > This is a fundamental error in how people think about this. Your > intuition is that you should try for a bigger win just in case - or > that it improves your overall winning chances. But if 10,000 monte > carlo playouts see one line as winning 10,000 times and another line > as winning 9,999 times, even if most of those wins are BIG, it will > choose the sure thing.
And maybe that cause them to lose more games. I understand the appeal of an elegant solution, but until we have such computing power that MC is practically identical to a complete game search, they will sometimes miss things, things that lose them a lot of points, or things that lose them some points. The latter doesn't matter if it has a significant lead that it hasn't thrown away. > Another way to look at it is this: If there are 2 key groups being > fought over, and winning either one wins the game, it will choose the > group that it is MOST likely to win - even if it is far smaller. > > There really is no way to improve on this except to trick it into NOT > maximizing it's winning probability. You might end up with a > program that appears to play more human, but it will sacrifice some > playing strength. Why would it lose playing strength by hedging its bets on making mistakes? Right now, if it plays under the assumption that it makes no mistakes (0.5 margin is enough to win the game), then some percentage X of the games will be lost because it misses things. If it plays under the assumption that it might make mistakes worth Y points (thus play as if a Y+0.5 point margin is needed to win the game), then it will in some percentage of games Z lose because it played too risky, took chances it didn't have to. If X<Z for all Y, then you are right. I don't think you are. The best strategy is probably to vary Y across the game, based on heuristics that are good at spotting situations where MC tend to miss things. _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
