Prescott, A.J. orcid.org/0000-0003-4927-5390, Camilleri, D., Martinez-Hernandez, U. et al. (2 more authors) (2019) Memory and mental time travel in humans and social robots. Philosophical Transactions B: Biological Sciences, 374 (1771). 20180025. ISSN 0962-8436
Abstract
From neuroscience, brain imaging, and the psychology of memory we are beginning to assemble an integrated theory of the brain sub-systems and pathways that allow the compression, storage and reconstruction of memories for past events and their use in contextualizing the present and reasoning about the future—mental time travel (MTT). Using computational models, embedded in humanoid robots, we are seeking to test the sufficiency of this theoretical account and to evaluate the usefulness of brain-inspired memory systems for social robots. In this contribution, we describe the use of machine learning techniques—Gaussian process latent variable models—to build a multimodal memory system for the iCub humanoid robot and summarise results of the deployment of this system for human-robot interaction. We also outline the further steps required to create a more complete robotic implementation of human-like autobiographical memory and MTT. We propose that generative memory models, such as those that form the core of our robot memory system, can provide a solution to the symbol grounding problem in embodied artificial intelligence.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. |
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) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - HORIZON 2020 785907 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 29 Jan 2019 15:40 |
Last Modified: | 21 Mar 2019 11:31 |
Status: | Published |
Publisher: | The Royal Society |
Refereed: | Yes |
Identification Number: | 10.1098/rstb.2018.0025 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:141650 |