Prescott, T.J. orcid.org/0000-0003-4927-5390, Vogeley, K. and Wykowska, A. orcid.org/0000-0003-3323-7357 (2024) Understanding the sense of self through robotics. Science Robotics, 9 (95). eadn2733. ISSN 2470-9476
Abstract
Robotics can play a useful role in the scientific understanding of the sense of self, both through the construction of embodied models of the self and through the use of robots as experimental probes to explore the human self. In both cases, the embodiment of the robot allows us to devise and test hypotheses about the nature of the self, with regard to its development, its manifestation in behavior, and the diversity of selves in humans, animals, and, potentially, machines. This paper reviews robotics research that addresses the topic of the self—the minimal self, the extended self, and disorders of the self—and highlights future directions and open challenges in understanding the self through constructing its components in artificial systems. An emerging view is that key phenomena of the self can be generated in robots with suitably configured sensor and actuator systems and a layered cognitive architecture involving networks of predictive models.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in Science Robotics is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Robotics; Humans; Animals; Equipment Design; Self Concept; Cognition; Ego; Artificial Intelligence |
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: | 11 Nov 2024 12:06 |
Last Modified: | 11 Nov 2024 15:12 |
Status: | Published |
Publisher: | American Association for the Advancement of Science (AAAS) |
Refereed: | Yes |
Identification Number: | 10.1126/scirobotics.adn2733 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:219433 |
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