2007/12/11, Don Dailey <[EMAIL PROTECTED]>: > Hi Petri, > > I happen to think that MC is the most human like approach currently > being tried
Ye in sense Alpha-Beta is human like. It one feature we do and takes it to extreme. And using different method of evaluation. . > > The reason I say that is that humans DO estimate their winning chances > and "tally" methods, where you simply tally up features/weights > (regardless of how sophisticated) is not how strong humans think about > the game. > Tallying up ius the non-human part. Extracting features and assigning meaning to them is very human. Good go player describe moves they make with terms like thicknes, wall, spere of influence,invasion..... Obviously these are not needed if one searches deep enough but how deep that would be? > game too. We may notice 3 moves that look playable, but gradually > come to focus on just 2 of those. Essentially monte carlo does this > too. Very narrow focused trees. Here we completely agree. It just picks the moves with different emphasis. And we do tactical analysis all the time. Something MC program is pretty weak at. I for instance played MOGO and it refused to resign until I places a dead group in atari. Any 20 would have seen that specific situation. Still that same 20 would have lost the game easily. So this is very unlike humans > > I attribute the success of MC to the fact that it's the best simulation > of how WE do it. The other approaches are clearly more synthetic, > including raw MC without a proper tree. > It could be the best but it is not very close. And adding more go knowledge to it may make it weaker by consuming CPU. There must be a third way. But this is the best idea that has posppoed up in years - or more like a decade > - Don > Petri _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/
