ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2019
Uncertainty and computational complexity.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Neural variability in the medial prefrontal cortex contributes to efficient adaptive behavior.Nature communications · 2025Article
- Action subsampling supports policy compression in large action spaces.PLoS computational biology · 2025Article
- Neural and behavioral signatures of policy compression in cognitive control.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Time and memory costs jointly determine a speed-accuracy trade-off and set-size effects.Journal of experimental psychology. General · 2025Article
- Neural and behavioral signatures of policy compression in cognitive control.bioRxiv : the preprint server for biology · 2025Article
- Resource-rational psychopathology.Behavioral neuroscience · 2024Review
- Suboptimal human inference can invert the bias-variance trade-off for decisions with asymmetric evidence.PLoS computational biology · 2022Article
- The use of cognitive task analysis in clinical and health services research - a systematic review.Pilot and feasibility studies · 2022Review
- Theory Before the Test: How to Build High-Verisimilitude Explanatory Theories in Psychological Science.Perspectives on psychological science : a journal of the Association for Psychological Science · 2021Article
- The computational cost of active information sampling before decision-making under uncertainty.Nature human behaviour · 2021Article
- Rational inattention and tonic dopamine.PLoS computational biology · 2021Article
- How Intractability Spans the Cognitive and Evolutionary Levels of Explanation.Topics in cognitive science · 2020Article
- Stochastic representation decision theory: How probabilities and values are entangled dual characteristics in cognitive processes.PloS one · 2020Article
- Risk taking and impulsive behaviour: fundamental discoveries, theoretical perspectives and clinical implications.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
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Authors and funding
3 authors.
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Abstract
Modern theories of decision-making typically model uncertainty about decision options using the tools of probability theory. This is exemplified by the Savage framework, the most popular framework in decision-making research. There, decision-makers are assumed to choose from among available decision options as if they maximized subjective expected utility, which is given by the utilities of outcomes in different states weighted with subjective beliefs about the occurrence of those states. Beliefs are captured by probabilities and new information is incorporated using Bayes' Law. The primary concern of the Savage framework is to ensure that decision-makers' choices are rational. Here, we use concepts from computational complexity theory to expose two major weaknesses of the framework. Firstly, we argue that in most situations, subjective utility maximization is computationally intractable, which means that the Savage axioms are implausible. We discuss empirical evidence supporting this claim. Secondly, we argue that there exist many decision situations in which the nature of uncertainty is such that (random) sampling in combination with Bayes' Law is an ineffective strategy to reduce uncertainty. We discuss several implications of these weaknesses from both an empirical and a normative perspective. This article is part of the theme issue 'Risk taking and impulsive behaviour: fundamental discoveries, theoretical perspectives and clinical implications'.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.