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Subject: Re: Evaluation at start versus eval at node. Why not mix them?

Author: Jon Dart

Date: 14:43:59 06/11/99

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On June 11, 1999 at 10:39:13, Dan Homan wrote:


>I've been thinking about this alot recently.  One thing that occurred
>to me is that this might be an effecient way to create a neural net based
>program.
>
>Say the neural net (nn) is responsible for filling a piece-square table...
>Then the nn could operate either once, at the root of the search, or
>only selected times during the search.  This would largely overcome
>the major drawback of nn evaluations which is that they are slow.
>
>Then we could have a TD based learning program that also learns
>evaluation features!
>
>I've thought alot about building my next chess program on this
>idea....  The one major drawback that I see is that there will be
>a relatively large number of parameters for learning to adjust.
>The other drawback is that I really know nothing useful about
>programming neural nets.  :)
>
> - Dan

KnightCap (http://samba.anu.edu.au/KnightCap/) has learning of
its evaluation parameters (as well as book learning) .. it
appears to work very well. But I don't believe it does non-leaf
evals.

--Jon



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