Lee, Jee Hang and Leibo, Joel Z. and An, Su Jin and Lee, Sang Wan (2022) Importance of prefrontal meta control in human-like reinforcement learning. Frontiers in Computational Neuroscience, 16. ISSN 1662-5188
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Abstract
Recent investigation on reinforcement learning (RL) has demonstrated considerable flexibility in dealing with various problems. However, such models often experience difficulty learning seemingly easy tasks for humans. To reconcile the discrepancy, our paper is focused on the computational benefits of the brain's RL. We examine the brain's ability to combine complementary learning strategies to resolve the trade-off between prediction performance, computational costs, and time constraints. The complex need for task performance created by a volatile and/or multi-agent environment motivates the brain to continually explore an ideal combination of multiple strategies, called meta-control. Understanding these functions would allow us to build human-aligned RL models.
Item Type: | Article |
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Subjects: | Euro Archives > Medical Science |
Depositing User: | Managing Editor |
Date Deposited: | 29 Mar 2023 04:02 |
Last Modified: | 29 Jan 2024 05:57 |
URI: | http://publish7promo.com/id/eprint/2158 |