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Subject: Re: chess and neural networks

Author: Christophe Theron

Date: 00:04:07 07/06/03

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On July 06, 2003 at 01:15:41, Uri Blass wrote:

>On July 06, 2003 at 00:25:49, Uri Blass wrote:
><snipped>
>>>Maybe using it for the evaluation is not the most efficient use of a neural
>>>network in a chess program. It seems that the way human players manage to search
>>>the tree is vastly underestimated.
>>>
>>>
>>>
>>>    Christophe
>>
>>I agree with you that search is underestimated in chess but I also believe
>>that search and evaluation are connected because a lot of search decisions are
>>based on evaluation of positions that are not leaf positions so you cannot
>>seperate them and say search improvement gives x elo and evaluation improvement
>>gives y elo.
>>
>>Uri
>
>I know that you did not try to seperate between them but my point is that if you
>want to do the same as humans in the search then changing the search is not
>enough.
>
>Humans may search position for some seconds and decide that this position is not
>good and later search the same position but decide that it is good for them not
>because they search deeper but because they learned to change their evaluation
>based on searching other lines that leaded to a similiar position.
>
>Uri



Well my point is just that when people talk about an application of ANN in chess
they always talk about implementing the evaluation with an ANN, or tuning the
evaluation with them.

I think it tends to show that the application of ANN to chess has never been
done by a "real" chess programmer. Because evaluation is only a part of a chess
program. And maybe not the one that can be improved dramatically, or that needs
them in order to be improved. Personally I would not use ANNs in the evaluation
first, because I think they would be much more efficient somewhere else.

On the other hand, you are right. If one could design an ANN to perform the
evaluation, it would be wise to use the same ANN (or an extension of it) to
guide the search.



    Christophe



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