My program is riddled with code to try and make use of this. (It's always bothered me that UCT relies on the standard deviation of (often) multi-modal distributions.) It hasn't made my engine any stronger but it has helped me understand some things better.
-----Original Message----- From: Dave Dyer <[EMAIL PROTECTED]> To: computer-go <computer-go@computer-go.org> Sent: Thu, 6 Dec 2007 3:13 pm Subject: [computer-go] Re: evaluating monte carlo results At 11:39 AM 12/6/2007, terry mcintyre wrote: >Any estimate of winning probability is only as good as the estimates of >whether particular games are actually won or lost. I propose that monte carlo programs should produce a distribution of quantitative outcomes rather than just a simple %win. It's only a very little more information to collect if you bin the outcomes in 10 point increments. Given this kind of data, you could prefer moves that had a narrower distribution of outcomes, and positively avoid those with bimodal distributions where 51% win big and 49% lose big. .. or it might be found that the distribution of outcomes is not a usable factor. _______________________________________________ computer-go mailing list computer-go@computer-go.org http://www.computer-go.org/mailman/listinfo/computer-go/ ________________________________________________________________________ More new features than ever. Check out the new AIM(R) Mail ! - http://o.aolcdn.com/cdn.webmail.aol.com/mailtour/aol/en-us/text.htm?ncid=aimcmp00050000000001
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