[Computer-go] Recursive Neural Networks

Lucas, Simon M sml at essex.ac.uk
Thu Jan 24 06:54:25 PST 2013


 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: computer-go-bounces at dvandva.org [mailto:computer-go-bounces at dvandva.org] On Behalf Of Petr Baudis
Sent: 24 January 2013 14:30
To: computer-go at dvandva.org
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
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