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Subject: Re: Automatic Eval Tuning

Author: Graham Laight

Date: 08:31:12 06/29/01

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On June 29, 2001 at 11:18:48, Vincent Diepeveen wrote:

>On June 29, 2001 at 11:14:34, Artem Pyatakov wrote:
>
>>I am curious, have people here experimented or extensively used Eval Function
>>tuning based on GM games for example?
>>
>>If so, is it effective to any extent?
>>
>>I came across this page and it seemed kind of interesting:
>>http://www.tim-mann.org/DT_eval_tune.txt
>>
>>Have others tried this too?
>>
>>Thanks in advance.
>
>yes i tried some years ago automatic tuning.
>
>The bigger your evaluation is, the more problematic tuning it automatic
>is. Also automatic tuners don't have any chess knowledge, so they
>don't see the difference between tuning passed pawns negative if you happen
>to have a testset where a passer is bad now and then.
>
>Another problem for automatic tuners is that you tune for testposition set X,
>but that in reality it has to work well also for testset Y where it has
>not been tuned for.
>
>Evaluations hand tuned take into account testset Y, not only testset X.
>
>Anyway, when your number of parameters gets quite a big number then
>automatic tuning doesn't work anyway anymore.
>
>Of course it might beat random chosen parameters, but it'll never beat
>hand chosen parameters (unless a fool choses them).
>
>Best regards,
>Vincent

Somebody is always doing something that somebody said couldn't be be done!

My opinion is that, if general machine learning is going to be achieved, then
things like this have to be solved. And general machine learning IS going to be
achieved. But it's going to take a lot of effort.

I think the key is that as well as allowing computers to tune evaluation
parameters, you also have to allow them to classify positions. Then, different
position types can give you different values for the same parameters.

However, the price you pay, when it comes to execution, is time. When evaluating
a position, the computer would have to select a position classification before
it could start to evaluate. Time is something contemporary chess programmers are
loathe to allow the computers to spend on position evaluation.

-g



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