[computer-go] Monte Carlo result as a feature for pattern matching

Don Dailey drd at mit.edu
Sat Jul 8 09:40:58 PDT 2006


Some of my programs in fact do measure expected ownership as a value
from -1.0 to 1.0.    In fact, you can bootstrap this knowledge to a
certain extent with benefit and my program does.

But unless you find a fuzzy way to do this with patterns,  there is
always the threshold problem.   Whatever "resolution" you choose you
will have cases that are on the boundary.    For instance you might have
3 cases:  clearly owned by black, neutral, and clearly owned by white.  
But there would be cases near the threshold.  A point might be "almost
clearly owned by white" for instance.

But I think it's probably a good idea if you can find a good way to
"generalize" patterns.   If you don't generalize, you have a huge number
of potential patterns.

- Don



On Sat, 2006-07-08 at 00:08 -0700, Peter Drake wrote:
> A number of researchers are using Monte Carlo Go as a way of  
> estimating the value of a given board position.
> 
> (For those of you not familiar with this technique, it involves  
> playing random moves to the end of the game and then counting the  
> score.  This is repeated many times and an average result taken.)
> 
> Pattern matchers regularly look at certain features such as the color  
> and edge/off-board status of each point within the pattern.  Some  
> pattern matchers look at more sophisticated features such as the  
> number of liberties a block has.
> 
> We would like to have access to life/death and influence information  
> in patterns.  For example, we would like to have patterns that say  
> things like "if a weak friendly stone shares a liberty with a strong  
> friendly stone, consider connecting them" or "if a point adjacent to  
> one of my stones is strongly influenced by me, playing on that point  
> is probably not important".
> 
> The problem is that open-ended life checkers and influence detectors  
> are quite difficult to write.
> 
> I propose (and am working on) using Monte Carlo analysis to find the  
> expected ownership of each point on the board (say, as a number in  
> the range [-1.0, 1.0]) and offering this information as a feature in  
> the pattern detector.
> 
> Thoughts?
> 
> Peter Drake
> Assistant Professor of Computer Science
> Lewis & Clark College
> http://www.lclark.edu/~drake/
> 
> 
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