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Subject: Re: chess and neural networks

Author: Christophe Theron

Date: 00:22:15 07/03/03

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On July 02, 2003 at 13:13:43, Landon Rabern wrote:

>On July 02, 2003 at 02:18:48, Dann Corbit wrote:
>
>>On July 02, 2003 at 02:03:20, Landon Rabern wrote:
>>[snip]
>>>I made an attempt to use a NN for determining extensions and reductions.  It was
>>>evolved using a GA, kinda worked, but I ran out of time. to work on it at the
>>>end of school and don't have my computer anymore. The problem is that the NN is
>>>SLOW, even using x/(1+|x|) for activation instead of tanh(x).
>>
>>Precompute a hyperbolic tangent table and store it in an array.  Speeds it up a
>>lot.
>
>Well, x/(1+|x|) is as fast or faster than a large table lookup.  The slowdown
>was from all the looping necessary for the feedforward.
>
>Landon



A stupid question maybe, but I'm very interested by this stuff:

Do you really need a lot of accuracy for the "activation function"? Would it be
possible to consider a 256 values output for example?

Would the lack of accuracy hurt?

I'm not sure, but it seems to me that biological neurons do not need a lot of
accuracy in their output, and even worse: they are noisy. So I wonder if low
accuracy would be enough.



    Christophe



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