Computer Chess Club Archives


Search

Terms

Messages

Subject: Re: chess and neural networks

Author: Dann Corbit

Date: 18:57:14 07/01/03

Go up one level in this thread


On July 01, 2003 at 18:28:19, Djordje Vidanovic wrote:

>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.

I think KnightCap is the most successful neural-net type of program.  Lots of
programs have some sort of learning, but neural nets are not used successfully
very often.

I think to work really well one would need:
1.  A very fast computer
2.  A very large number of evaluation terms
3.  A very long time slot after a loss so that the calculations could be
absorbed into the eval.

I know some other people working on neural nets, and I think the results are
interesting.

The early attempts (e.g. Sal) were unfathomably lame.  But then again, so are
the early attempts at anything and everything.

The question is:
Can a neural net make a program play better?
I think the answer is pretty clearly "Yes!"

The more salient question is:
Is there a more effective way to make a program play better?
I don't think that question has been answered or even can be answered.

That's just one of the things that makes chess programming so interesting.



This page took 0.02 seconds to execute

Last modified: Thu, 07 Jul 11 08:48:38 -0700

Current Computer Chess Club Forums at Talkchess. This site by Sean Mintz.