Path: utzoo!utgpu!news-server.csri.toronto.edu!clyde.concordia.ca!uunet!decwrl!ucbvax!ucsd!sdcc6!zaius!pluto From: pluto@zaius.ucsd.edu (Mark Plutowski) Newsgroups: comp.ai.neural-nets Subject: Re: Observations on the State of NN theory Keywords: Genetic Neural Training Pepsi Message-ID: <12173@sdcc6.ucsd.edu> Date: 4 Aug 90 23:48:03 GMT References: <1990Aug3.175023.28210@ariel.unm.edu> Sender: news@sdcc6.ucsd.edu Organization: CSE Dept., U. C. San Diego Lines: 40 Nntp-Posting-Host: zaius.ucsd.edu In article <1990Aug3.175023.28210@ariel.unm.edu> bill@hooey.unm.edu (william horne) writes: >In article spoffojj@hq.af.mil (Jason Spofford) writes: SPOFFORD: I would like to hear some reactions to the following generalizations: ... SPOFFORD: I'd like to think I'm attacking the metaproblem of NN's, SPOFFORD: artificially developing NN's in a way not too unlike biological SPOFFORD: systems. HOOEY Writes: Here's my $0.02..... I don't think GAs have much to offer for learning techniques in networks ... which have a good gradient search technique for learning [or] use floating point weight representations. ... My experience with GAs have been that they are terrible at searching the bizarre error surfaces ... in fact they are no better than a completely random search. This seems to be due to the fact that the bits in floating point representations are highly correlated with each other. There are things you can do to avoid this, ...... but not to the point where they are competitive with a simple gradient search. I don't see [GAs] as particularly appropriate for learning algorithms ... ... In any case I don't think they are the global solution to NN learning. > >Feel free to flame this... > >-Bill Well, OK, if you insist! Actually, this is not much of a flame, but more of a memo that GAs can help a great deal, with that one aspect of network learning we all know and love: The Restart Method! Yes, you too have used it, if you've done any network training at all. Now, what's wrong with utilizing a bit of knowledge (or, a byte or two even) from past restarts to guide the settings of parameters and initial weights for the next one? GAs can do this. Now if they could only get the population counts down...