ArticlePLoS computational biology2024
Human decision making balances reward maximization and policy compression.
Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Computationally Informed Insights Into Anhedonia and Treatment by Kappa Opioid Receptor Antagonism.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025Trial
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- Suboptimal human inference reflects an efficient and flexible information bottleneck.bioRxiv : the preprint server for biology · 2026Article
- Representational capacity shapes both the "whether" and "how" of social learning.PLoS computational biology · 2026Article
- Recurrent Neural Network Exploration Strategies During Reinforcement Learning Depend on Network Capacity.Computational brain & behavior · 2026Article
- Dorsal prefrontal cortex drives perseverative behavior in mice.Nature communications · 2026Article
- The adaptive tasks and trade-offs that drive the human value system.Communications psychology · 2025Article
- Acute stress impairs decision-making at varying levels of decision complexity.Communications psychology · 2025Article
- Action repetition biases choice in context-dependent decision-making.Communications psychology · 2025Article
- Evolving choice hysteresis in reinforcement learning: Comparing the adaptive value of positivity bias and gradual perseveration.Proceedings of the National Academy of Sciences of the United States of America · 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
- Policy Complexity Suppresses Dopamine Responses.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- A Rational Framework for Group-Based Selective Social Learning.Open mind : discoveries in cognitive science · 2025Article
- An algorithmic account for how humans efficiently learn, transfer, and compose hierarchically structured decision policies.Cognition · 2025Article
- Policy complexity suppresses dopamine responses.bioRxiv : the preprint server for biology · 2024Article
- Active reinforcement learning versus action bias and hysteresis: control with a mixture of experts and nonexperts.PLoS computational biology · 2024Article
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Authors and funding
2 authors.
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Abstract
Policy compression is a computational framework that describes how capacity-limited agents trade reward for simpler action policies to reduce cognitive cost. In this study, we present behavioral evidence that humans prefer simpler policies, as predicted by a capacity-limited reinforcement learning model. Across a set of tasks, we find that people exploit structure in the relationships between states, actions, and rewards to "compress" their policies. In particular, compressed policies are systematically biased towards actions with high marginal probability, thereby discarding some state information. This bias is greater when there is redundancy in the reward-maximizing action policy across states, and increases with memory load. These results could not be explained qualitatively or quantitatively by models that did not make use of policy compression under a capacity limit. We also confirmed the prediction that time pressure should further reduce policy complexity and increase action bias, based on the hypothesis that actions are selected via time-dependent decoding of a compressed code. These findings contribute to a deeper understanding of how humans adapt their decision-making strategies under cognitive resource constraints.
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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.