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METHODS article

Front. Psychol.
Sec. Cognitive Science
Volume 15 - 2024 | doi: 10.3389/fpsyg.2024.1438581
This article is part of the Research Topic The Cognitive Basis for Decision Making Under Risk and Uncertainty: Research Programs & Controversies View all 9 articles

Stochastic heuristics for decisions under risk and uncertainty

Provisionally accepted
Leonidas Spiliopoulos Leonidas Spiliopoulos *Ralph Hertwig Ralph Hertwig
  • Max Planck Institute for Human Development, Berlin, Germany

The final, formatted version of the article will be published soon.

    Models of heuristics are often predicated on the desideratum that they should possess no free parameters. As a result, heuristic implementations are usually deterministic and do not allow for any choice errors, as the latter would require a parameter to regulate the magnitude of errors. We discuss the implications of this in light of research that highlights the evidence supporting stochastic choice and its dependence on preferential strength. We argue that, in principle, the existing models of deterministic heuristics should, and can, be quite easily modied to stochastic counterparts through the addition of an error mechanism. This requires a single free parameter in the error mechanism, whilst otherwise retaining the parameter-free cognitive processes in the deterministic component of existing heuristics. We present various types of error mechanisms applicable to heuristics and discuss their comparative virtues and drawbacks, paying particular attention to their impact on model comparisons between heuristics and parameter-rich models.

    Keywords: Errors, Decision making under risk and uncertainty, Model Comparison, Stochastic heuristics, bounded rationality

    Received: 26 May 2024; Accepted: 15 Jul 2024.

    Copyright: © 2024 Spiliopoulos and Hertwig. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Leonidas Spiliopoulos, Max Planck Institute for Human Development, Berlin, Germany

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