Does natural selection favour the Rescorla-Wagner rule?

Pete C. Trimmer, John M. McNamara, Alasdair I. Houston, James A. R. Marshall

Research output: Contribution to journalArticle (Academic Journal)peer-review

35 Citations (Scopus)

Abstract

A fundamental question relating to animal behaviour is how animals learn; in particular, how they come to associate stimuli with rewards. Numerous empirical findings can be explained by assuming that animals use some mechanism similar to the Rescorla-Wagner learning rule, which is a relatively simple and highly general method of updating the associative strength between different stimuli. However, the Rescorla-Wagner rule is often not optimal, which raises the question of why a rule with such properties should have evolved. We consider the evolution of learning rules in a simple environment where there exists an optimal rule of similar complexity to the Rescorla-Wagner rule. We show that because the Rescorla-Wagner rule is less sensitive to changes in its parameters than the optimal rule, there is a wider range of parameter values over which the rule structure is initially viable. Consequently, the Rescorla-Wagner rule can be favoured by natural selection, ahead of other rules which are more accurate. (C) 2012 Elsevier Ltd. All rights reserved.

Original languageEnglish
Pages (from-to)39-52
Number of pages14
JournalJournal of Theoretical Biology
Volume302
DOIs
Publication statusPublished - 7 Jun 2012

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