Re: [computer-go] Noise reduction in alpha-beta search

2007-04-10 Thread Chrilly 
Ingo Althoeffer has published some time ago a theoretical article about this 
idea. He called it telescope evaluation. According his theorectical findings 
is the error propagation not better than the usual approach.
K.Chen proposed a similar approach. Use the mean of the last and second-last 
evaluation. I tried this. It makes the search more stable. With the normal 
search we have strong odd/even effects. At odd depths Suzie evaluates the 
position (considerable) higher than at even depths. At odd depths Suzie has 1 
move more in the variation than the opponent. This odd/even effect disappears 
with the K.Chen mean. Also the search depth increases, because move ordering is 
more stable. But the result in the autoplay-matches was worse. One gets effects 
like the following: 1 Ply before the horizon the opponent makes a threat. The 
evaluation goes down considerable, but there is a defense move and at the 
horizon nothing has happened.. But according the mean the programm is still in 
some trouble. Or if one reverses the role, Suzie would like to play the 
threat-move. This scheme increases therefore even the potential of the programm 
to cheat. 

Chrilly

  - Original Message - 
  From: [EMAIL PROTECTED] 
  To: computer-go@computer-go.org 
  Sent: Monday, April 09, 2007 4:48 PM
  Subject: [computer-go] Noise reduction in alpha-beta search


  I think following is a way to reduce the noise in alpha-beta search. Instead 
of using the evaluation values, use the cummulative evaluation values. That is 
the sum of the evaluation values of each node of the playing path under 
examination.


  Daniel Liu

--
  AOL now offers free email to everyone. Find out more about what's free from 
AOL at AOL.com.



--


  ___
  computer-go mailing list
  computer-go@computer-go.org
  http://www.computer-go.org/mailman/listinfo/computer-go/___
computer-go mailing list
computer-go@computer-go.org
http://www.computer-go.org/mailman/listinfo/computer-go/

Re: [computer-go] Noise reduction in alpha-beta search

2007-04-10 Thread Chrilly 
It can't be. He was probably studying the general game, not Go

Ingo Althoefer published his results in the context of chess. Alpha-Beta Search 
was until recently not a topic in Go (besides its not possible).

The score in Go is additive, if the score is territory.

But that is not a possible evaluation function. E.g. in the first stages only 
on small parts of the board is white/black territory defined. The rest is 
influence/Moyo (or nothing). One needs also some notion of weakness of a group. 
The All or Nothing (Group is Living or Death) approach does not work. There 
must be some evaluations/stages in between. If a weak group controls some 
territory, this territory should also count less...

This problem is to be solved by deeper search.
Yes. But it is very difficult to find reasonable quiet criterions. One has to 
stop the search at one point, because otherwise it explodes. 

Chrilly
  - Original Message - 
  From: [EMAIL PROTECTED] 
  To: computer-go@computer-go.org 
  Sent: Tuesday, April 10, 2007 5:23 PM
  Subject: Re: [computer-go] Noise reduction in alpha-beta search


  It can't be. He was probably studying the general game, not Go. The score in 
Go is additive, if the score is territory. 2-steps approach make some sense, 
but not in general situation. At each step the pendlum swings to one side is 
the nature of the game. Nothing wrong with it. One gets the same problem with 
single step evaluation too. This problem is to be solved by deeper search.

  Daniel Liu

   
  -Original Message-
  From: [EMAIL PROTECTED]
  To: computer-go@computer-go.org
  Sent: Tue, 10 Apr 2007 1:46 AM
  Subject: Re: [computer-go] Noise reduction in alpha-beta search


  Ingo Althoeffer has published some time ago a theoretical article about this 
idea. He called it telescope evaluation. According his theorectical findings 
is the error propagation not better than the usual approach.

  Chrilly

- Original Message - 
From: [EMAIL PROTECTED] 
To: computer-go@computer-go.org 
Sent: Monday, April 09, 2007 4:48 PM
Subject: [computer-go] Noise reduction in alpha-beta search


I think following is a way to reduce the noise in alpha-beta search. 
Instead of using the evaluation values, use the cummulative evaluation values. 
That is the sum of the evaluation values of each node of the playing path under 
examination.


Daniel Liu


AOL now offers free email to everyone. Find out more about what's free from 
AOL at AOL.com.




___
computer-go mailing list
computer-go@computer-go.org
http://www.computer-go.org/mailman/listinfo/computer-go/
___
computer-go mailing list
computer-go@computer-go.org
http://www.computer-go.org/mailman/listinfo/computer-go/


--


  ___
  computer-go mailing list
  computer-go@computer-go.org
  http://www.computer-go.org/mailman/listinfo/computer-go/___
computer-go mailing list
computer-go@computer-go.org
http://www.computer-go.org/mailman/listinfo/computer-go/