harnad@phoenix.Princeton.EDU (S. R. Harnad) (06/16/89)
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