ArticleProceedings of the National Academy of Sciences of the United States of America2023
Overharvesting in human patch foraging reflects rational structure learning and adaptive planning.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Foraging models explain human exploration in uncertain tasks.Nature communications · 2026Article
- A specific computational role for early-life unpredictability, and not lifelong traumatic experience, in decision-making under uncertainty.bioRxiv : the preprint server for biology · 2026Article
- Stochastic choice drives variability in patch foraging decisions in humans and rats.Communications psychology · 2026Article
- Multistep inference across the human lifespan can be improved with individualized memory interventions.The journals of gerontology. Series B, Psychological sciences and social sciences · 2026Article
- Review
- Human foraging strategies flexibly adapt to resource distribution and time constraints.Cognitive, affective & behavioral neuroscience · 2026Article
- Planning to be incremental: Scene descriptions reveal meaningful clustering in language production.Cognition · 2026Article
- Rats pursue food and leisure following the same rational principles.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- Reward-reset interval timing drives patch foraging decisions through neural state transitions in dorsomedial striatum.bioRxiv : the preprint server for biology · 2025Article
- Stochastic decisions support optimal foraging of volatile environments, and are disrupted by anxiety.Cognitive, affective & behavioral neuroscience · 2025Article
- Article
- One factor to bind them all: visual foraging organization to predict patch leaving behavior with ROC curves.Cognitive research: principles and implications · 2025Article
- Foraging animals use dynamic Bayesian updating to model meta-uncertainty in environment representations.PLoS computational biology · 2025Article
- Risk preferences depend on environmental richness in rats performing a patch-foraging task.bioRxiv : the preprint server for biology · 2025Article
- A framework for uniting space and time in the mind and brain.Frontiers in cognition · 2025Article
- Increasing Response Vigour Under Time Pressure as a Transdiagnostic Marker of Eating Disorders.Computational psychiatry (Cambridge, Mass.) · 2025Review
- No matter what you do, travel is travel in visual foraging.Vision research · 2024Article
- Architectural styles of curiosity in global Wikipedia mobile app readership.Science advances · 2024Article
- Cognitive Graphs: Representational Substrates for Planning.Decision (Washington, D.C.) · 2024Article
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2 authors.
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Abstract
Patch foraging presents a sequential decision-making problem widely studied across organisms-stay with a current option or leave it in search of a better alternative? Behavioral ecology has identified an optimal strategy for these decisions, but, across species, foragers systematically deviate from it, staying too long with an option or "overharvesting" relative to this optimum. Despite the ubiquity of this behavior, the mechanism underlying it remains unclear and an object of extensive investigation. Here, we address this gap by approaching foraging as both a decision-making and learning problem. Specifically, we propose a model in which foragers 1) rationally infer the structure of their environment and 2) use their uncertainty over the inferred structure representation to adaptively discount future rewards. We find that overharvesting can emerge from this rational statistical inference and uncertainty adaptation process. In a patch-leaving task, we show that human participants adapt their foraging to the richness and dynamics of the environment in ways consistent with our model. These findings suggest that definitions of optimal foraging could be extended by considering how foragers reduce and adapt to uncertainty over representations of their environment.
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