Classical conditioning via inference over observable situation contexts

Nisheeth SrivastavaUniversity of California, San Diego
Paul SchraterUniversity of Minnesota

Abstract

In this paper, we demonstrate that predicting stimulus co-occurrence patterns in a Bayes-optimal manner endogenously explains classical conditioning. Simulated experiments with a standard Bayesian implementation of this model show that it is capable of explaining a broader range of effects than any previous theory of classical conditioning. By simplifying the mathematical structure of statistical modelling of conditioning and demonstrating its ability to explain a large set of experimentally observed effects, our work advances Bayes-optimal inference about stimulus co-occurrence as a rational principle explaining classical conditioning.

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