Decision-making in brains and robots - the case for an interdisciplinary approach
Accepted version
Repository URI
Repository DOI
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Authors
Lee, Sang Wan
Abstract
Reinforcement Learning describes a general method for trial-and-error learning, and has emerged as a dominant framework both for optimal control in autonomous robots, and understanding decision-making in the brain. Despite their common roots, however, these two fields have evolved largely independently. In this perspective we consider how each now face problems that could potentially be addressed by insights from the other, and argue that an interdisciplinary approach could greatly accelerate progress in both.
Description
Keywords
5202 Biological Psychology, 32 Biomedical and Clinical Sciences, 3209 Neurosciences, 52 Psychology, Neurosciences, Mental health
Journal Title
Current Opinion in Behavioral Sciences
Conference Name
Journal ISSN
2352-1546
2352-1546
2352-1546
Volume Title
26
Publisher
Elsevier Limited
Publisher DOI
Sponsorship
Wellcome Trust (097490/Z/11/Z)
Arthritis Research UK (21192)
Arthritis Research UK (21537)
Arthritis Research UK (21192)
Arthritis Research UK (21537)