[Computer-go] 7.0 Komi and weird deep search result

Brian Sheppard sheppardco at aol.com
Tue Apr 5 09:29:08 PDT 2011

I don't know if the worst could be worse; UCT convergence for a 1-ply search
is a probabilistic function with an exponential bound. The bound for an
N-ply search is a tower of N exponentials: Exp(Exp(Exp(...Exp()))). Ugh.

Because of this bound, guessing good moves quickly is absolutely vital for
strong play from UCT. Which calls into question why I haven't taken MM and
Sim Balancing more seriously. :-)

-----Original Message-----
From: computer-go-bounces at dvandva.org
[mailto:computer-go-bounces at dvandva.org] On Behalf Of Petr Baudis
Sent: Monday, April 04, 2011 10:27 PM
To: computer-go at dvandva.org
Subject: Re: [Computer-go] 7.0 Komi and weird deep search result

On Mon, Apr 04, 2011 at 12:56:54PM -0400, Brian Sheppard wrote:
> >> MCTS using RAVE prioritization *does* converge to game theoretic values
> in a
> >> binary-valued space.
> >Can you reference some more detailed analysis claiming this?
> Theorem: In a binary-valued game of finite length, the RAVE score of all
> winning moves converges to 1, provided that 0 < FPU < 1.

Oh of course, it is obvious. Sorry for being slow and confused.

But it seems it should be possible to prove that even theoretical
convergence in case of RAVE discrepecancies is much slower than with
plain UCT... Might be a fun exercise.

				Petr "Pasky" Baudis
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