I am very interested in reading a detailed description of your results. -----Original Message----- From: [email protected] [mailto:[email protected]] On Behalf Of Hendrik Baier Sent: Monday, July 11, 2011 5:47 PM To: [email protected] Subject: Re: [Computer-go] Computer-go Digest, Vol 18, Issue 29
>On 19x19, Many Faces has books. A full board opening book made from strong >player games is a hash of all positions (rotation/refection invariant). It >keeps statistics of player strength and win rate, and is only used to bias >the search, not to choose a move quickly. That's what I re-invented recently, and I combined it with a joseki book made from strong player games as well. Both books just recommend a bunch of moves, the appropriate choice is left to the search algorithm. Because I don't return a move instantly without search, I call it "active book application". So far (without any kind of parameter tuning or manual changes to the book) it increased Orego's win rate against GNUGo by 4-5 percent, with 10 seconds per move. I wonder if the effect would be stronger or weaker for a stronger program - it's more difficult to improve a stronger program of course, but it might also understand some of the openings better and make better use of them. A clean, hand-coded book of joseki might be very strong in this framework, but I don't have the time. Thanks everybody for your answers. I might post a short paper about this soon if people are interested. _______________________________________________ Computer-go mailing list [email protected] http://dvandva.org/cgi-bin/mailman/listinfo/computer-go _______________________________________________ Computer-go mailing list [email protected] http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
