If it's true, it's an indication of the properties of the game tree 
distrubution. If a first move is good, it leads to a favorable geometric 
position. Starting from a geometricaly favorable position more good random 
playing lines exist than bad random playing line(the number of the good random 
playing lines plus the number of the bad random playing lines equal to the 
total number of all possible playing lines). Actually the ladder may not be an 
exception. At each step of a ladder there are only two possible moves. One good 
and one may not be good. The chance is 50% or larger.
 
Daniel Liu

-----Original Message-----
From: [EMAIL PROTECTED]
To: [email protected]
Sent: Sun, 11 Mar 2007 2:03 PM
Subject: [computer-go] when to stop searching


On 3/11/07, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote: 
 
But to pick the best move, it's "only" necessary to recognize the 
weaknesses in all the other moves. In many cases these weaknesses can 
be recognized using move sequences that are far less than perfect 
play. The tricky part seems to be sequences can only be evaluated 
with perfect play for many moves such as ladders. It's unclear how 
often such perfection is required to pick the best move. 
 
> Thus, one starts with an imperfect subset of moves and an imperfect 
> evaluation function and feed them to a search algorithm (alpha-beta, for 
> example). In general, the higher are the merit probabilities, the more 
> effective is the search. 
 
With UTC, if I understand correctly, it would eventually try every 
possible sequence, but of course not within the time limit, so it 
isn't clear that it starts with an "imperfect subset of moves" that is 
separate from the other factors. 
 
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