4.1 Article

Equilibria of the Rescorla-Wagner model

Journal

JOURNAL OF MATHEMATICAL PSYCHOLOGY
Volume 47, Issue 2, Pages 109-121

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/S0022-2496(02)00016-0

Keywords

Rescorla-Wagner model; causal learning

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The Rescorla-Wagner 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 Rescorla-Wagner model with more recent models have been hampered by the fact that the Rescorla-Wagner 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 Rescorla-Wagner model impact the long-run behavior of the model. (C) 2003 Elsevier Science (USA). All rights reserved.

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