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Optimal utility and probability functions for agents with finite computational precision.

Keno Juechems1,2, Jan Balaguer1, Bernhard Spitzer3

  • 1Department of Experimental Psychology, Radcliffe Observatory, OX2 6GG Oxford, United Kingdom; keno.juchems@psy.ox.ac.uk juan.delojobalaguer@psy.ox.ac.uk spitzer@mpib-berlin.mpg.de christopher.summerfield@psy.ox.ac.uk.

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Summary
This summary is machine-generated.

Human economic choices show distorted value and probability representations. These distortions, caused by finite computational precision and noise, are actually optimal for maximizing reward and minimizing uncertainty.

Keywords:
computational precisionprospect theoryuncertaintyutility

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Area of Science:

  • Cognitive Science
  • Behavioral Economics
  • Decision Neuroscience

Background:

  • Humans exhibit distorted value and probability representations in economic choices.
  • These distortions lead to decisions that appear suboptimal and preferences that reverse inexplicably.
  • The evolutionary basis for these

Purpose of the Study:

  • To explain why humans evolve distorted value and probability encoding despite selective pressure for reward maximization.
  • To demonstrate that observed human decision-making distortions are approximately optimal under finite computational precision.
  • To investigate how humans adapt their decision strategies when reward-maximizing distortions are manipulated.

Main Methods:

  • Modeling economic decision-making under the assumption of finite computational precision (noise).
  • Empirical manipulation of factors influencing reward-maximizing distortions in decision-making.
  • Analysis of human adaptation to altered distortion parameters in controlled studies.

Main Results:

  • Finite computational precision (noise) naturally leads to distortions in value and probability representation.
  • These distortions are shown to be approximately optimal for maximizing reward and minimizing uncertainty.
  • Human participants demonstrated optimal adaptation to manipulated factors affecting decision distortions.

Conclusions:

  • The apparent irrationality in human economic choices can be explained by optimal adaptation to computational noise.
  • Distorted value and probability encoding is a consequence of, and an optimal strategy for, decision-making with limited precision.
  • This framework offers a resolution to the long-standing question of non-reward-maximizing economic behavior.