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According to normative theories, reward-maximizing agents should have consistent preferences. Thus, when faced with alternatives A, B, and C, an individual preferring A to B and B to C should prefer A to C. However, it has been widely argued that humans can incur losses by violating this axiom of transitivity, despite strong evolutionary pressure for reward-maximizing choices. Here, adopting a biologically plausible computational framework, we show that intransitive (and thus economically irrational) choices paradoxically improve accuracy (and subsequent economic rewards) when decision formation is corrupted by internal neural noise. Over three experiments, we show that humans accumulate evidence over time using a "selective integration" policy that discards information about alternatives with momentarily lower value. This policy predicts violations of the axiom of transitivity when three equally valued alternatives differ circularly in their number of winning samples. We confirm this prediction in a fourth experiment reporting significant violations of weak stochastic transitivity in human observers. Crucially, we show that relying on selective integration protects choices against "late" noise that otherwise corrupts decision formation beyond the sensory stage. Indeed, we report that individuals with higher late noise relied more strongly on selective integration. These findings suggest that violations of rational choice theory reflect adaptive computations that have evolved in response to irreducible noise during neural information processing.

Original publication

DOI

10.1073/pnas.1519157113

Type

Journal article

Journal

Proc Natl Acad Sci U S A

Publication Date

15/03/2016

Volume

113

Pages

3102 - 3107

Keywords

choice optimality, decision making, evidence accumulation, irrationality, selective integration, Adolescent, Adult, Choice Behavior, Decision Theory, Feedback, Psychological, Female, Form Perception, Games, Experimental, Humans, Judgment, Male, Middle Aged, Models, Economic, Models, Psychological, Photic Stimulation, Psychophysics, Reward, Video Games, Young Adult