Inference and search on graph-structured spaces

Abstract excerpt

How do people learn functions on structured spaces? And how do they use this knowledge to guide their search for rewards in situations where the number of options is large? We study human behavior on structures with graph-correlated values and propose a Bayesian model of function learning to describe and predict their behavior. Across two experiments, one assessing function learning and one assessing the search fo...

Topics

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• Catechol O-Methyltransferase
• Learning
• Memory, Short-Term
• Models, Neurological
• Photic Stimulation
• Psychomotor Performance
• Receptors, G-Protein-Coupled
• Reinforcement, Psychology

Identifiers and source

Literature Corpus work

b3afcf8d-284c-5609-8445-ce7edd2bd2e7

DOI

10.1101/2020.03.06.981399