It would be interesting to see the actual formulas used for choosing the more to try in the tree part of the search.
For Many Faces, it is: (1 – beta) * (win_rate + 0.45 * sqrt( ln(parent_visits) / child visits)) + beta * rave_win_rate + mfgo_bias beta is the old Mogo formula of sqrt(500/(500 + 3 * parent_visits)) A child with no visits has a win_rate of 1.1. Otherwise there is no win_rate bias. rave wins and visits are strongly biased when moves are generated using various rules and information from the mfgo move generator (in a range of 10% to 90% win rate, with hundreds to thousands of visits). mfgo_bias is unchanging, per move, within a range of about +-2%, based on mfgo’s move generator’s estimate of the quality of the move. Does anyone else want to share? David From: computer-go-boun...@dvandva.org [mailto:computer-go-boun...@dvandva.org] On Behalf Of Fuming Wang Sent: Saturday, January 01, 2011 9:00 AM To: Aja; email@example.com Subject: Re: [Computer-go] Fwd: News on Tromp-Cook ? Hi Aja, On Sun, Jan 2, 2011 at 12:16 AM, Aja <ajahu...@gmail.com> wrote: Hi Fuming, Most of the current strong programs are using UCT combined with RAVE (a kind of AMAF). The formula is like this (there are many variants), C*RAVE+(1-C)*UCT This has been my understanding. However, I am surprized to find out that people have been setting C close to one, according to Petr and Oliver's postings, which is essentially AMAF. MF apparently is doing something different. Fuming
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