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Subject: Re: chess and neural networks

Author: Djordje Vidanovic

Date: 15:28:19 07/01/03

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On July 01, 2003 at 15:35:22, Charles Roberson wrote:

>
>  KnightCapp uses neural networks and I beleive some papers were published
>  about it.
>
>  ICCA Journal vol 14 September 1991 has a paper "Neural Networks as a Guide
>  to Optimization" by A. van Tiggelen. It discusses automated tuning of a
>  position evaluator.
>
>   Charles


KnightCap is pretty good at learning both opening lines and evals. I finally
managed to compile it to run well on my Linux box and I started it without any
brain.dat actually and with default coeffs.dat.  In a little while it started
beating Gnuchess (say after about 400 blitz games) and even managed to win
several games against Crafty.  It IS getting stronger, but of course its limits
are close   because the search parameters have to be better. Although some
programmers do think that its qsearch is fine...

I find KnightCap a lot of fun, especially its "mulling" over the losing lines
and finding out better lines while idle.  I find it an extremely tough opponent,
as tough, if not tougher than some well known programs.  After about 500 blitz
games it started beating Scidlet as well.  Scidlet is considered to be about
2200, so I'd venture to say that KnightCap progressed from a 1900 player to a
2250 player in about 500 games.  There are a couple of papers on KnightCap in
pdf format, by Andrew Tridgell and Jonathan Baxter.  And, of course, the famous
paper on Temporal Difference learning by Rich Sutton that started it all.  All
can be found on the Net.

Neural learning seems to be quite succesful in games that require fewer
parameters than chess, such as backgammon (JellyFish, GnuBackgamon, BGBlitz) or
checkers.  Chess is tough as it has lots of parameters that matter.

Djordje




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