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

Aja ajahuang at gmail.com
Tue Apr 5 18:45:00 PDT 2011


I don't think your current work is not valuable, and fully agree with you 
that MM/SB-based engines have a much greater effect on strength, which is 
clearly proved by Erica. But recently my feeling is that current MCTS almost 
reaches its limit on 19x19. We will need another breakthrough/good ideas to 
overcome KGS 5d or 6d.

Aja

----- Original Message ----- 
From: "Brian Sheppard" <sheppardco at aol.com>
To: <computer-go at dvandva.org>
Sent: Wednesday, April 06, 2011 7:00 AM
Subject: Re: [Computer-go] 7.0 Komi and weird deep search result


>I spend a lot of time on computer Go, but probably not in the right places.
>
> My work currently focuses on expressing positional features using 3x3 
> neighborhoods, so that domain knowledge is easier to express as data 
> rather than if/else code. This is useful stuff, to be sure.
>
> Instead, I really ought to build two systems: an MM-based engine to 
> prioritize moves in the tree search, and an SB-based engine for random 
> search in the playout. I am sure that these would have a much greater 
> effect on strength.
>
> But I started the other effort, and I should continue for a while before 
> changing. Probably I will do MM next.
>
> Brian
>
> -----Original Message-----
> From: computer-go-bounces at dvandva.org 
> [mailto:computer-go-bounces at dvandva.org] On Behalf Of Aja
> Sent: Tuesday, April 05, 2011 1:35 PM
> To: computer-go at dvandva.org
> Subject: Re: [Computer-go] 7.0 Komi and weird deep search result
>
> 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: computer-go at dvandva.org
> 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: 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
> _______________________________________________
> Computer-go mailing list
> Computer-go at dvandva.org
> http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
>
> _______________________________________________
> Computer-go mailing list
> Computer-go at dvandva.org
> http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
>
> _______________________________________________
> Computer-go mailing list
> Computer-go at dvandva.org
> http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
>
> _______________________________________________
> Computer-go mailing list
> Computer-go at dvandva.org
> http://dvandva.org/cgi-bin/mailman/listinfo/computer-go 




More information about the Computer-go mailing list