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Subject: Re: How To Use Neural Networks In Chess - Use Lots Of Them!

Author: Will Singleton

Date: 23:49:00 06/22/00

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On June 23, 2000 at 02:03:45, Bruce Moreland wrote:

>On June 23, 2000 at 01:13:09, Will Singleton wrote:
>
>>On June 22, 2000 at 21:35:02, Graham Laight wrote:
>>
>>>When we've discussed NNs in the past, as far as I remember (and excuse me if
>>>I've missed some threads where this has already been discussed), we've always
>>>discussed them in terms of creating one giant, monolithic NN.
>>>
>>>In a flash of inspiration last night, it suddenly occured to me that what you
>>>actually need is one NN for each type of "positional factor" you are trying to
>>>recognise.
>>>
>>>For example, you could build a NN of an appropriate size, and train it to look
>>>out for cases where a "smothered mate" was likely to become possible - using a
>>>set of positions where it either is, or isn't likely. Then, for each node that
>>>is to be evaluated in a game, you can pass that position to this NN, and come up
>>>with an assessment of whether this particular positional weakness (or strength!)
>>>exists.
>>>
>>>When you have got 50,000 such NNs working, then "vous voila!" - you have your
>>>player with grandmaster level skill.
>>
>>>I think that this would be a good use for multiple processor (or multiple
>>>computer) systems. And, in reality, wouldn't it be a good model for how the
>>>human brain works?
>>>
>>>In summary, instead of thinking about one big NN, think about having lots of
>>>little NNs to play chess with.
>>>
>>>-g
>>
>>I think your idea has a lot of merit, but not sure this is a new idea.  I also
>>think it could take years to design a system to coordinate a set of eval
>>functions which could choose the proper neural weight set (or sets).  Would be a
>>process of tuning the training function, then playing games to judge the result,
>>then modifying the training function and generating new weights.
>>
>>It might be very difficult to get this to work.  NN's seem to work best where a
>>huge set of games can be used to figure out the training function params, and
>>the resulting weights.  Lots of trial and error.  Chess doesn't lend itself well
>>to such training.
>>
>>Will
>
>I think there is little substance to this idea, and furthermore I expect that
>there is little truth to the notion that this has anything to do with human
>thought.
>
>A series of in-parallel recognizers.  Fine.  But there is absolutely nothing
>about how to relate them, and only one pattern out of 50,000 proposed patterns
>is enumerated.
>
>We have the title for yet another novel, but I would like to see the first
>chapter, or at least the first paragraph, before I consider giving Graham a cash
>advance.
>
>bruce

Agreed.

There's an interesting article at
http://www.lucent.com/press/0600/000621.bla.html

Not really relative to this particular discussion, but perhaps in the future...

Will




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