Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!csd4.milw.wisc.edu!indri!polyslo!usc!brand.usc.edu!manj From: manj@brand.usc.edu (B. S. Manjunath) Newsgroups: comp.ai.neural-nets Subject: Re: request for philosophic reactions to connectionism Keywords: ART, Grossberg Message-ID: <16722@usc.edu> Date: 23 Apr 89 19:48:13 GMT References: <370@eurtrx.UUCP| <18496@gatech.edu> <7894@phoenix.Princeton.EDU> <18504@gatech.edu> <7903@phoenix.Princeton.EDU> <1@bucsb.UUCP> <1775@Portia.Stanford.EDU> Sender: news@usc.edu Reply-To: manj@brand.usc.edu (B. S. Manjunath) Distribution: usa Organization: University of Southern California, Los Angeles, CA Lines: 40 kortge@portia.stanford writes: >>In article <1@bucsb.UUCP> adverb@bucsb.bu.edu (Josh Krieger) writes: >>Please stop dismissing ART out of ignorance! >> >[deleted] >Good analogy. Notice that even though I don't understand microprocessor >intricacies, I can still program a computer. Grossberg seems very >concerned with the physical implementation of his systems, and thus >includes a lot of complicated mathematical detail. There's nothing ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ >objectively wrong with this, but a lot of it may be unneccessary for >describing the essential information-processing properties, and keeps >"ignorant" people at a distance. Unfortunately ! Also I would like to add that most of it is unnecessary too . All the analysis that is carried out in the paper (BTW I am referring to the paper by Carpenter and Grossberg, " A Massively Parallel ....", CVGIP 1987, pp. 54 - 115 = -61 !) makes many simplifying assumptions. The STM dynamics is completely ignored and it is assumed to be in the equilibrium state whenever a pattern is presented. See for eg. Section 18 ( Yes - Eighteen/27) of the paper. >The advantages: > [4 advantages deleted] >> 5) ART has a vast amount of solid psychological and biological >> evidence for its existence. This probably is the strongest point in favour of ART. However I am yet to completely "decode" the ART2 ( For analog patterns). Simulations seem to work but I see no reason for so many layers within F1. I understand that the system does some kind of normalization of the input patterns but I fail to see why so many of them are needed. Could anyone comment on this ? >Chris Kortge bs manjunath manj@brand.usc.edu