On Mon, Jun 14, 2010 at 3:59 PM, Mark Boon <[email protected]> wrote:
> But I'm not sure how the method you're describing is any different > from what old programs like Goliath used to do. There's a step in pattern recognition called "feature extraction", where you decide what information to encode, and how to scale that info so that you get a useful way of representing features that you want to represent. At the same time, some information must be discarded. (Unless each of your patterns represents a total board state!) I'm sure you already knew that. So, while there might not be a difference in _what_ the old programs used to do and in _what_ Tim's approach does, there could yet be a difference in _how_ it's done. That is, perhaps there is some clever representation of a behavior in go, for which we may select and encode and scale various features, and also for which we may discard much unnecessary or redundant information, with the end-result that _my_ patterns take more into account (and hence are more useful) than your patterns did, back in the old days. Which is to say, the "feature extraction" phase may be the crucial phase. I can't speak for Tim Maguire, but I share his suspicion that Monte Carlo may not be the best way to achieve dan-level play. I believe (and hope to someday demonstrate, but there's still a lot of work to be done) that dan-level programs will _severely_ prune the game-tree via the use of pattern-classification, and then use simple minimax on the remaining candidate moves (as Tim described). (One could also use a Monte-Carlo layer in the program, but with this severely-pruned tree, minimax is probably "enough".) The tricky parts are: 1) Extracting just those features we want (and throwing others away as unnecessary or redundant), and 2) being able to compare an arbitrary pattern to others that we may have seen in the past (likely, during observation of professional games, as that is the behavior we wish to emulate). -- Rich _______________________________________________ Computer-go mailing list [email protected] http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
