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Subject: Re: Local optima / genetic algorithms

Author: Komputer Korner

Date: 14:53:26 08/03/98

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On August 03, 1998 at 16:57:04, James Long wrote:

>As I rewrite my program, I've been seriously considering
>trying a genetic algorithm to train the evaluation
>function.  I've got a pretty good grasp on how to
>handle this, but a couple of things are still
>bothering me:
>
>Most programmers hand tune their eval functions, either
>themselves or with the help of a strong player.  Is
>this because the results are generally better, or
>because a good learning eval is difficult to write?
>Dr. Hyatt - do you think Crafty may be in a state
>of local optima?  (Or do you use a learning eval?)
>Bruce?  Anybody? :-)  I'm wondering how many
>programs get caught up on this.
>
>For the program to "learn," the eval variables must
>mutate dependent on the outcome of a game.  One approach
>I read about is to set up a tournament of 100 "players,"
>each player having random values assigned to its
>eval terms (with the exception of the pawn score).
>When one player finally wins, the weakest player's
>terms are modified.  This requires thousands of games,
>but I'm in no hurry.  My question is - how to go about
>modifying the eval terms.  I've got a couple ideas,
>but I'd like to read more.  Anybody got some good
>pointers??
>
>
>---
>James

Read the June issue of the ICCA journal re: the article "Experiments in
Parameter Tuning using Temporal Differences". The ICCA journal has an ISSN
number 0920-234X.
--
Komputer Korner



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