Prefrontal meta-control incorporating mental simulation enhances the adaptivity of reinforcement learning agents in dynamic environments

These findings advance our understanding of computational reinforcement learning whilst contributing to the development of brain-inspired learning agents capable of flexible, goal-directed behavior within dynamic environments.

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Publication Details

Journal
Frontiers in Computational Neuroscience
Published
2025-03-27
DOI
https://doi.org/10.3389/fncom.2025.1559915
Primary Topic
Reinforcement Learning in Robotics
Type
article
Field-Weighted Citation Impact
0.00
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article

Prefrontal meta-control incorporating mental simulation enhances the adaptivity of reinforcement learning agents in dynamic environments

J.-H. Kim, Jee Hang Lee
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Frontiers in Computational Neuroscience
Reinforcement Learning in Robotics
article

Prefrontal meta-control incorporating mental simulation enhances the adaptivity of reinforcement learning agents in dynamic environments

J.-H. Kim, Jee Hang Lee
article en

Abstract

These findings advance our understanding of computational reinforcement learning whilst contributing to the development of brain-inspired learning agents capable of flexible, goal-directed behavior within dynamic environments.

Frontiers in Computational NeuroscienceVol. 19
Korea Institute for Advanced Study (KR), Sangmyung University (KR)
Peace, Justice and strong institutions
Openalex Percentile: Top 97%
Reinforcement Learning in Robotics
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