title: Rationalizable irrationalities of choice.
abstract: Although seemingly irrational choice abounds, the rules governing these mis-steps that might provide hints about the factors limiting normative behavior are unclear. We consider three experimental tasks, which probe different aspects of non-normative choice under uncertainty. We argue for systematic statistical, algorithmic, and implementational sources of irrationality, including incomplete evaluation of long-run future utilities, Pavlovian actions, and habits, together with computational and statistical noise and uncertainty. We suggest structural and functional adaptations that minimize their maladaptive effects.
authors.affiliation: Gatsby Computational Neuroscience Unit, University College London.
authors.forename: Peter
authors.initials: P
authors.lastname: Dayan
mesh_terms: D000465:Algorithms; D002755:Choice Behavior / Q000502:physiology*; D003657:Decision Making / Q000502:physiology*; D006801:Humans; D008962:Models, Theoretical; D011908:Rationalization; D035501:Uncertainty
keywords: Bounded rationality; Model-based; Model-free; Noisy decision-making; Pavlovian; Pruning; Reinforcement learning