Prescott, T.J. orcid.org/0000-0003-4927-5390 and Wilson, S.P. orcid.org/0000-0001-8125-5133 (2023) Understanding brain functional architecture through robotics. Science Robotics, 8 (78). eadg6014. ISSN 2470-9476
Abstract
Robotics is increasingly seen as a useful test bed for computational models of the brain functional architecture underlying animal behavior. We provide an overview of past and current work, focusing on probabilistic and dynamical models, including approaches premised on the free energy principle, situating this endeavor in relation to evidence that the brain constitutes a layered control system. We argue that future neurorobotic models should integrate multiple neurobiological constraints and be hybrid in nature.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 the author(s). This is an author-produced version of a paper subsequently published in Science Robotics. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Jun 2023 11:25 |
Last Modified: | 05 Jun 2023 17:05 |
Status: | Published |
Publisher: | American Association for the Advancement of Science (AAAS) |
Refereed: | Yes |
Identification Number: | 10.1126/scirobotics.adg6014 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:199900 |