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Noa L. Hedrich

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Articles by Noa L. Hedrich

An inductive bias for slowly changing features in human reinforcement learning

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By Noa L. Hedrich, Universität Hamburg, Charité Universitätsmedizin Berlin, Eric Schulz
| PLOS
Loading metrics Open Access Peer-reviewed Research Article ? This is an uncorrected proof. Citation: Hedrich NL, Schulz E, Hall-McMaster S, Schuck NW (2024) An inductive bias for slowly changing features in human reinforcement learning. PLoS Comput Biol 20(11): e1012568. https://doi.org/10.1371/journal.pcbi.1012568 Editor: Stefano Palminteri, Ecole Normale Superieure, FRANCE Received: January 21, 2024; Accepted: October 17, 2024; Published: November 25, 2024 Copyright: © 2024 Hedrich et al.
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An inductive bias for slowly changing features in human reinforcement learning

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By Eric Schulz, Nicolas W. Schuck, Noa L. Hedrich
| BioRxiv
Abstract Identifying goal-relevant features in novel environments is a central challenge for efficient behaviour. We asked whether humans address this challenge by relying on prior knowledge about common properties of reward-predicting features. One such property is the rate of change of features, given that behaviourally relevant processes tend to change on a slower timescale than noise. Hence, we asked whether humans are biased to learn more when task-relevant features are slow rather than fast.
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