Author: Vincent Diepeveen
Date: 17:38:09 07/02/03
Go up one level in this thread
On July 02, 2003 at 12:44:56, Ingo Lindam wrote:
>
>> b) they do not work very well for situations they are not trained for
>> and in chess you always explore new positions which are not trained yet,
>> which is an easy thing to understand once you understand that chess has
>> 10^44 positions and you could train perhaps for 10^2 positions at
>> most very well so missing around 10^40 somewhere.
>
>I am not voting for using NNs for chess, but is b) a fair agrument?
>Isn't it sufficient to see all significant features of positions often enough.
>Also a GM doesn't see 10^44 positions before he starts to play as a GM.
>Ofcourse the GM does obtain and evaluate some very concrete lines. And I don't
>suggest neither a human being nor a computer to play chess without calculating
>concrete lines. (As well as I would not suggest to play chess without having
>plans and aims and some kind of chess knowledge)
Actually this problem is caused by 2 reasons
a) they get imperfect trained
b) all of the training algorithms are assuming the above b argument.
that's why NNs work for voice recognition a bit, as you usually have
the same voice, but they do not work for evaluatoin of chess positions
in playing programs because it is each time a new situation.
It has no understanding like you and i do, all it has is a few
stupid parameters that it can tune. that's it. It doesn't even know
what a parameter influences in fact. It is all experiments that are
independant from each other. That's a real weakness trivially.
>Internette Gruesse,
>Ingo
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