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Economic irrationality is optimal during noisy decision making.

Konstantinos Tsetsos1, Rani Moran2, James Moreland3

  • 1Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, United Kingdom; Department of Psychological Sciences, Birkbeck, University of London, London WC1E 7HX, United Kingdom; k.tsetsos62@gmail.com.

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Humans sometimes make economically irrational choices, but this intransitivity can improve decision accuracy. This selective integration strategy helps overcome internal neural noise, suggesting adaptive evolution in decision-making processes.

Keywords:
choice optimalitydecision makingevidence accumulationirrationalityselective integration

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Area of Science:

  • Cognitive Neuroscience
  • Behavioral Economics
  • Computational Neuroscience

Background:

  • Normative theories predict consistent preferences (transitivity) for reward-maximizing agents.
  • Human decision-making often violates the axiom of transitivity, leading to economic losses.
  • Evolutionary pressure favors reward maximization, yet intransitive choices persist.

Purpose of the Study:

  • To investigate how intransitive choices can paradoxically improve accuracy and rewards.
  • To explore the role of internal neural noise in decision formation.
  • To test a biologically plausible computational framework for decision-making.

Main Methods:

  • Developed a computational framework modeling decision formation with neural noise.
  • Conducted three experiments to observe evidence accumulation using a 'selective integration' policy.
  • Performed a fourth experiment to confirm predictions of transitivity violations in human observers.

Main Results:

  • Selective integration, discarding lower-value information, predicts intransitive choices under specific conditions.
  • Human observers showed significant violations of weak stochastic transitivity.
  • Higher levels of 'late' neural noise correlated with stronger reliance on selective integration.

Conclusions:

  • Intransitive choices are not necessarily irrational but can be adaptive computations.
  • Selective integration protects decisions against late-stage neural noise.
  • Violations of rational choice theory reflect evolved strategies for noisy neural processing.