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.

Keywords: Bounded rationality; Model-based; Model-free; Noisy decision-making; Pavlovian; Pruning; Reinforcement learning.