I might not really catch what you meant, but I wonder why. :)
Aja
-----原始郵件-----
From: Brian Sheppard
Sent: Wednesday, April 06, 2011 12:29 AM
To: [email protected]
Subject: Re: [Computer-go] 7.0 Komi and weird deep search result
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: [email protected]
[mailto:[email protected]] On Behalf Of Petr Baudis
Sent: Monday, April 04, 2011 10:27 PM
To: [email protected]
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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