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Journal of Mathematical Psychology 47 (2003) 109121 Equilibria of the RescorlaWagner model
 

Summary: Journal of Mathematical Psychology 47 (2003) 109­121
Equilibria of the Rescorla­Wagner model
David Danks*
Institute for Human & Machine Cognition, University of West Florida, 40 S. Alcaniz St., Pensacola, FL 32501, USA
Received 30 October 2000; revised 17 January 2002
Abstract
The Rescorla­Wagner model has been a leading theory of animal causal induction for nearly 30 years, and human causal
induction for the past 15 years. Recent theories (especially Psychol. Rev. 104 (1997) 367) have provided alternative explanations of
how people draw causal conclusions from covariational data. However, theoretical attempts to compare the Rescorla­Wagner
model with more recent models have been hampered by the fact that the Rescorla­Wagner model is an algorithmic theory, while the
more recent theories are all computational. This paper provides a detailed derivation of the long-run behavior of the Rescorla­
Wagner model under a wide range of parameters and experimental setups, so that the model can be compared with computational
theories. It also shows that the model agrees with competing theories on a wider range of cases than had previously been thought.
The paper concludes by showing how recently suggested modifications of the Rescorla­Wagner model impact the long-run behavior
of the model.
r 2003 Elsevier Science (USA). All rights reserved.
Keywords: Rescorla­Wagner model; Causal learning
1. Introduction
Rescorla and Wagner (1972) presented a model to
explain some unusual results in animal learning. The

  

Source: Andrews, Peter B. - Department of Mathematical Sciences, Carnegie Mellon University

 

Collections: Mathematics