Humans learn generalizable representations through efficient coding

Abstract Reinforcement learning theory explains human behavior as driven by the goal of maximizing reward. Conventional approaches, however, offer limited insights into how people generalize from past experiences to new situations. Here, we propose refining the classical reinforcement learning frame...

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Bibliographic Details
Main Authors: Zeming Fang, Chris R. Sims
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-58848-6
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