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[computer-go] RE: Scalability



My simple answer to your question below is that Q-search in go are
responses to "disturbing moves". Most of these moves are bad sente
moves. For example meaningless peeps or attacks on keimas that cannot be
cut.

If you make a 1-ply search without pruning such bad moves the evaluation
function (well at least the one I programmed) will return a high score
for all those moves. 
A q-search would respond with those simple local moves that repairs the
damage and even shows a gain for the defender. 

So Q-search in go would be more of repairing the shape of stable groups
rather than life and death and captures.

My program Viking does this by matching patterns to centered on each
move played in 1ply full board look ahead. If a Q-detection pattern
matches then it will make a local response (effectively 2-ply locally).
It also does a 1-ply search with similar replies if necessary for all
opponent moves. In order to detect strong attacks that has no strong
response.

This work very well compared to a simple 1-ply search and is faster than
a 2-ply search, but often it breaks down in complex fighting (but which
go program does not have that problem?)

--
Magnus Persson
Center for Adaptive Behavior and Cognition
Tel: +49-(30)-82406-350
Cell phone: +49 163 6639868

> -----Original Message-----
> From: Don Dailey [mailto:drd@xxxxxxxxxxxxxxxxx]
> 
> >  So at least in principle traditional chess techniques work in go
but
> >  since you only can search 2 ply with a complex evaluation function
all
> >  the cool chess stuff such as null moves and transposition tables
has no
> >  impact.
> 
> Yes, it seems so.  But I'm not even sure what the term "quiescence
> search" really means in Go.  It is really an ambigious term to
> describe a kind of "selectivity done just before leaf nodes."


> Are some of you guys using such a search in your GO programs?  I'm not
> talking about the highly localized life/death searches which isn't in
> the spirit of giving a quiet board.
> 
> - Don
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