AUTHOR=Lee Jee Hang , Leibo Joel Z. , An Su Jin , Lee Sang Wan 

TITLE=Importance of prefrontal meta control in human-like reinforcement learning

JOURNAL=Frontiers in Computational Neuroscience

VOLUME=16

YEAR=2022

URL=https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2022.1060101

DOI=10.3389/fncom.2022.1060101

ISSN=1662-5188

ABSTRACT=<p>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.</p>