[computer-go] thoughts on 100,000 cgos games

[Aidan Karley]

In article <EC419E85-AF89-4060-ACFB-8EC0B8294B18 at mac.com>, David G 
Doshay wrote:
> I can think of no solid way to benefit from an automated approach
> given only the information that I lost all of these games.
>
       Would concentrating on those lost games to process out 
additional metrics help? For example, classifying the lost games by 
number of groups (winner), ratio of #groups(winner) : #groups(loser), 
points of territory/group, number of eyes/group. Wouldn't that 
(potentially) give you more information about the types of error you're 
making, e.g. allowing the opponent to split your groups while 
connecting their groups (emphasised by the #groups ratio above), or 
allowing groups to be squeezed too much (reduced points of territory 
per group metric)?
       Has anyone tried defining such metrics, and proposed some styles 
of play that can be differentiated on the basis of such metrics? Would 
such metrics, if they work, be a useful contribution to the information 
theory aspects of computer go, rather than specifically assisting 
development of a particular program.
       
-- 
 Aidan Karley,
 Aberdeen, Scotland,
 Location: 57°10' N,  02°09'  W (sub-tropical Aberdeen), 0.021233
 Written at Sun, 07 May 2006 21:46 +0100