title: Bayesian theories of conditioning in a changing world.
abstract: The recent flowering of Bayesian approaches invites the re-examination of classic issues in behavior, even in areas as venerable as Pavlovian conditioning. A statistical account can offer a new, principled interpretation of behavior, and previous experiments and theories can inform many unexplored aspects of the Bayesian enterprise. Here we consider one such issue: the finding that surprising events provoke animals to learn faster. We suggest that, in a statistical account of conditioning, surprise signals change and therefore uncertainty and the need for new learning. We discuss inference in a world that changes and show how experimental results involving surprise can be interpreted from this perspective, and also how, thus understood, these phenomena help constrain statistical theories of animal and human learning.
authors.affiliation: Département d'Informatique et de Recherche Opérationnelle, Université de Montréal, Montréal, QC H3C 3J7, Canada. courvila@iro.umontreal.ca
authors.forename: Aaron C
authors.initials: AC
authors.lastname: Courville
authors.forename: Nathaniel D
authors.initials: ND
authors.lastname: Daw
authors.forename: David S
authors.initials: DS
authors.lastname: Touretzky
mesh_terms: D000818:Animals; D001245:Association Learning; D001499:Bayes Theorem; D001522:Behavior, Animal; D003214:Conditioning, Classical; D005108:Extinction, Psychological; D006801:Humans; D007266:Inhibition, Psychological; D011340:Problem Solving; D012055:Reinforcement Schedule; D012922:Social Change; D012931:Social Environment; D013269:Stochastic Processes; D035501:Uncertainty