ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2023
Undermatching Is a Consequence of Policy Compression.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2023. 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.
- Computationally Informed Insights Into Anhedonia and Treatment by Kappa Opioid Receptor Antagonism.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025Trial
- Reduced Pavlovian Value Updating Alters Decision-Making in Sign-Trackers.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026Article
- Time-dependent deployment of medial prefrontal cortical representations in male mice.Nature communications · 2026Article
- Environmental dynamics impact whether matching is optimal.PNAS nexus · 2026Article
- Time and memory costs jointly determine a speed-accuracy trade-off and set-size effects.Journal of experimental psychology. General · 2025Article
- Policy Complexity Suppresses Dopamine Responses.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Policy complexity suppresses dopamine responses.bioRxiv : the preprint server for biology · 2024Article
- Surprising sounds influence risky decision making.Nature communications · 2024Article
- Resource-rational psychopathology.Behavioral neuroscience · 2024Review
- Human decision making balances reward maximization and policy compression.PLoS computational biology · 2024Article
- The role of rat prelimbic cortex in decision making.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
- Bayesian Reinforcement Learning With Limited Cognitive Load.Open mind : discoveries in cognitive science · 2024Article
- Mechanisms of adjustments to different types of uncertainty in the reward environment across mice and monkeys.Cognitive, affective & behavioral neuroscience · 2023Article
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Authors and funding
2 authors.
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Abstract
The matching law describes the tendency of agents to match the ratio of choices allocated to the ratio of rewards received when choosing among multiple options (Herrnstein, 1961). Perfect matching, however, is infrequently observed. Instead, agents tend to undermatch or bias choices toward the poorer option. Overmatching, or the tendency to bias choices toward the richer option, is rarely observed. Despite the ubiquity of undermatching, it has received an inadequate normative justification. Here, we assume agents not only seek to maximize reward, but also seek to minimize cognitive cost, which we formalize as policy complexity (the mutual information between actions and states of the environment). Policy complexity measures the extent to which the policy of an agent is state dependent. Our theory states that capacity-constrained agents (i.e., agents that must compress their policies to reduce complexity) can only undermatch or perfectly match, but not overmatch, consistent with the empirical evidence. Moreover, using mouse behavioral data (male), we validate a novel prediction about which task conditions exaggerate undermatching. Finally, in patients with Parkinson's disease (male and female), we argue that a reduction in undermatching with higher dopamine levels is consistent with an increased policy complexity.
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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.