Path: utzoo!attcan!utgpu!jarvis.csri.toronto.edu!rutgers!njin!princeton!phoenix!harnad
From: harnad@phoenix.Princeton.EDU (S. R. Harnad)
Newsgroups: comp.ai
Subject: Proper Place of Connectionism
Keywords: Categorization, Behavioral Capacity, Feature Detection
Message-ID: <9016@phoenix.Princeton.EDU>
Date: 16 Jun 89 06:09:24 GMT
Organization: Princeton University, NJ
Lines: 29


ON THE PROPER PLACE OF CONNECTIONISM IN MODELLING OUR BEHAVIORAL CAPACITIES

(Abstract of paper presented at First Annual Meeting of the American
Psychological Society, Alexandria VA, June 11 1989)

Stevan Harnad, Psychology Department, Princeton University, Princeton NJ 08544

Connectionism is a family of statistical techniques for extracting
complex higher-order correlations from data. It can also be interpreted
and implemented as a neural network of interconnected units with
weighted positive and negative interconnections. Many claims and
counterclaims have been made about connectionism: Some have said it
will supplant artificial intelligence (symbol manipulation) and
explain how we learn and how our brain works. Others have said it is
just a limited family of statistical pattern recognition techniques and
will not be able to account for most of our behavior and cognition. I
will try to sketch how connectionist processes could play a crucial 
but partial role in modeling our behavioral capacities in learning and
representing invariances in the input, thereby mediating the "grounding"
of symbolic representations in analog sensory representations. The
behavioral capacity I will focus on is categorization: Our ability to
sort and label inputs correctly on the basis of feedback from the
consequences of miscategorization.
-- 
Stevan Harnad  INTERNET:  harnad@confidence.princeton.edu   harnad@princeton.edu
srh@flash.bellcore.com      harnad@elbereth.rutgers.edu    harnad@princeton.uucp
CSNET:    harnad%confidence.princeton.edu@relay.cs.net
BITNET:   harnad1@umass.bitnet      harnad@pucc.bitnet            (609)-921-7771