Nice paper in IEEE Conference on Computational Intelligence and Games 2012 that compares Remi's method with Stern et al and some others:
"Comparison of Bayesian Move Prediction Systems for Computer Go" Martin Wistuba, Lars Schaefers, and Marco Platzner The paper is normally available for free download from the CIG 2012 web site: http://geneura.ugr.es/cig2012/ but the server seems to be down at the moment so I've just put it here temporarily: http://dces.essex.ac.uk/staff/sml/tmp/cig2012MovePredictionGo.pdf Simon Lucas -----Original Message----- From: [email protected] [mailto:[email protected]] On Behalf Of Petr Baudis Sent: 24 January 2013 14:30 To: [email protected] Subject: Re: [Computer-go] Recursive Neural Networks On Wed, Jan 23, 2013 at 04:41:57PM -0500, George Dahl wrote: > This paper reports 36% move prediction accuracy: > http://www.cs.utoronto.ca/~ilya/pubs/2008/go_paper.pdf C.f. also http://research.microsoft.com/apps/pubs/default.aspx?id=67955 which reports 34% accuracy for top move, 66% accuracy for top five moves suggested. I'm not sure if anyone measured Remi Coulom's pattern model performance in move prediction. P.S.: As already mentioned, it should go without saying that there is very little correlation if any between move prediction rate and playing strength as a sole move generator or a feature provider. Petr "Pasky" Baudis _______________________________________________ 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
