Re: [computer-go] Minimax with random evaluations

[Don Dailey <drd@xxxxxxx>]

>    I think these findings are very intriguing. But how about putting this
>    a bit more to the test, and compare '5 ply random' against '5 ply
>    legal-move-count'? 

What is 5 ply legal-move-count?  Are you suggesting that I use number
of legal moves as an evaluation function, say the difference between
black and white move counts?  I could do this,  but no matter what the
result I don't see how it would help resolve anything in my mind.

What would you conclude if say ...

    1) move count did much better.
    2) move count did much worse?

My intuition is that in chess, move count would be much stronger than 
random evaluation because it is a more or less direction measurement
of mobility,  a very important concept.   

I also believe move-counts, if it's what I think you are saying, would
be a lot better in GO than random evaluation.  It would cause a
program to want to make a lot of 1 point eyes (because they are
illegal for the opponent to move into, thus the computer would be
happy to keep a point alive that only it could move into.  This of
course assumes suicide is illegal.

I'm thinking random evaluation has a similar effect and may be the
main benefit, but not to the same extent as move-count mobility.  Just
a guess, I don't really know.

- Don






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   Date: Mon, 24 Jan 2005 17:06:32 +0100
   From: Mark Boon <tesujisoftware@xxxxxxxxxxxxxxxxx>
   Reply-To: Mark Boon <tesujisoftware@xxxxxxxxxxxxxxxxx>
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   On Mon, 24 Jan 2005 08:11:45 -0500, Don Dailey <drd@xxxxxxxxxxxxxxxxx> wrote:
   > 
   > >  In many games having lots of move options correlates somewhat with
   > >  a good position. But, as noted previously, this is not very
   > >  relevant in the context of go.
   > 
   > It looks like it may be relevant in GO too.  Of course this depends on
   > what you mean by relevant.
   > 
   > Random evaluation is a very poor evaluation in any reasonable game you
   > choose, but the interesting result is that random evaluation combined
   > with a search leads to something much better than completely aimless
   > play.
   > 
   > In my tests of 5x5 Go, 5 ply random evaluation beats random play with
   > an 81% score over 1000 games.
   > 
   > In 7x7 Go, 5 ply random evaluation beats random play with an 82.4%
   > score over 523 games.
   > 
   > Not very impress when you consider the huge amount of extra work being
   > done, but quite impressive when you consider the evaluation function
   > used!
   > 

   I think these findings are very intriguing. But how about putting this
   a bit more to the test, and compare '5 ply random' against '5 ply
   legal-move-count'? That may remove the doubt from your "It looks like
   it may be" statement above. If your assumption is correct, the latter
   should have a 50+ winning percentage, possibly also up to 80%.

   As to the relevance: when I have more time I may write something more
   elaborate on this, but I think from previous posts here it's obvious
   the relevance is fairly high. There have been some arguments that more
   reading didn't improve the level of play due to the fact the
   evaluation function was too unreliable. Your experiment may give a
   better boundary to how unreliable it needs to be to get worse play
   when reading deeper. Or it may show that that argument has been
   completely false all the time, and the reason has to be looked for
   elsewhere.

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