What are the advantages and distadvantages to predicate logic and NNs? Dan Goe
---------------------------------------------------- >From : Yan King Yin <[EMAIL PROTECTED]> To : agi@v2.listbox.com Subject : Re: [agi] How the Brain Represents Abstract Knowledge Date : Wed, 14 Jun 2006 04:28:36 +0800 > > What I said in my previous reply was that something very like neural nets > > (with all the beneficial features for which people got interested in NNs > in > > the first place) *can* do syntax, and all forms of abstract > representation. > > > > I do not think it is fair to say that they can't, only that the > > particularly restrictive interpretation of NN that prevails in the > > literature can't. > Hi Richard > > I have to agree that NN can represent all forms of knowledge, since our > brains are NNs. But figuring out how to do that in artificial systems must > be pretty difficult. I should also mention Ron Sun's work, he has > long tried to reconcile neural and symbolic processing. I studied NNs/ANNs > for some time, but I recently switched camp to the more symbolic side. > > One question is whether there is some definite advantage to using NNs > instead of say, predicate logic. Can you give an example of a thought, or a > line of inference, etc, that the NN-type representation is particularly > suited? And that has a advantage over the predicate logic representation? > John McCarthy proposed that predicate logic can represent 'almost' > everything. > > If NN-type representation is not necessarily required, then we should > naturally use symbolic/logic representations since they are so much more > convenient to program and to run on von Neumann hardware. > > YKY > > ------- > To unsubscribe, change your address, or temporarily deactivate your subscription, > please go to http://v2.listbox.com/member/[EMAIL PROTECTED] ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
