What value of K is used with many simulations.  It seems that with millions
of simulations, a small value for K will make little difference.

David

> -----Original Message-----
> From: computer-go-boun...@computer-go.org [mailto:computer-go-
> boun...@computer-go.org] On Behalf Of Darren Cook
> Sent: Tuesday, October 06, 2009 12:06 AM
> To: computer-go
> Subject: Re: [computer-go] Progressive widening vs unpruning
> 
> > I tried this yesterday with K=10 and it seemed to make Many Faces weaker
> > (84.2% +- 2.3 vs 81.6% +-1.7), not 95% confidence, but likely weaker.
> This
> > is 19x19 vs gnugo with Many Faces using 8K playouts per move, 1000 games
> > without and 2000 games with the change.  I have the UCT exploration
> term, so
> > perhaps with exploration this idea doesn't work.  Or perhaps the K I
> tried
> > is too large.
> 
> If I understood correctly Olivier described it (*) as being the most
> important term when using a large number of simulations. How about
> trying 8 million playouts instead of 8 thousand...
> 
> Which brings up the question of how to reliably evaluate changes when
> using a high number of playouts.
> 
> Darren
> 
> *: Olivier wrote:
> What we call "progressive unpruning" is termed "progressive bias" by Rémi
> Coulom. It is the use of a score which is a linear combination between
> 1) expert knowledge
> 2) patterns (in 19x19)
> 3) rave values
> 4) regularized success rate (nbWins +K ) /(nbSims + 2K)
> (the original "progressive bias" is simpler than that)
> 
> for small numbers of simulations, 1) and 2) are the most important;
> 3) become important later; and 4) is, later, the most important term.
> 
> 
> --
> Darren Cook, Software Researcher/Developer
> http://dcook.org/gobet/  (Shodan Go Bet - who will win?)
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