Connectionism and Classical Conditioning

by Michael R.W. Dawson,
University of Alberta

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Abstract

The purpose of this monograph is to examine the relationship between a particular artificial neural network, the perceptron, and the Rescorla-Wagner model of learning. It is shown that in spite of the fact that there is a formal equivalence between the two, they can make different predictions about the outcomes of a number of classical conditioning experiments. It is argued that this is due to algorithmic differences the two, differences which are separate from their computational equivalence.

Dawson, M. R. W. (2008). Connectionism and Classical Conditioning. Comparative Cognition & Behavior Reviews, 3. Retrieved from http://comparative-cognition-and-behavior-reviews.org/ doi:10.3819/ccbr.2008.30008