Yes, you are right. Now I understand how those Monte Carlo programs works.

I modified my question (and email subject) as:

On average how many board updates/sec can top conventional Go programs do
these days?


On Jan 14, 2008 8:48 PM, David Doshay <[EMAIL PROTECTED]> wrote:

> The problem here is that you asked mutually contradictory things. You
> defined what you meant by a board update, in which you specified a
> list of things, and you also asked about "top programs." The top
> programs do not do the kinds of evaluations you specify, although
> older conventional programs do. The newer programs that are now the
> strongest are variations of the Monte Carlo method, which does
> statistical sampling, not the kinds of evaluation you specify.
>
> Cheers,
> David
>
>
>
> On 14, Jan 2008, at 7:41 PM, mingwu wrote:
>
> > On Jan 14, 2008 6:15 PM, Jason House <[EMAIL PROTECTED]>
> > wrote:
> >
> > slow.  UCT (or generically Monte Carlo) can "evaluate" a position
> > fairly
> > quickly (maybe 1k-100k per second depending on how heavy the playout
> > is), they don't give a reliable estimate.  To improve this, they
> > end up
> >
> > 1K ~ 100 K / sec is much faster than "a dozen" / sec of a
> > conventional program.
> >
> > Do they calculate dragon safety (eyes, connections, patterns ...)?
> > if not, the estimate will be VERY unreliable.
> > But if they do, how can they be this fast compared to the more
> > conventional programs?
> >
> > reevaluating positions more than once (maybe 100 times?) to get a more
> > reliable estimate.
> >
> > why "reevaluating" the same position?
> >
> > Sorry, I didn't go into their papers, can people who knows UCT, or
> > actually working on UCT programs explain in a way that a layman can
> > understand.  Thanks.
> >
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