Theory of Mind and Preference Learning at the Interface of Cognitive Science, Neuroscience, and AI: A Review.
artificial intelligence
cognitive and neuroscience
human theory of mind
inverse reinforcement learning
machine theory of mind
Journal
Frontiers in artificial intelligence
ISSN: 2624-8212
Titre abrégé: Front Artif Intell
Pays: Switzerland
ID NLM: 101770551
Informations de publication
Date de publication:
2022
2022
Historique:
received:
17
09
2021
accepted:
10
03
2022
entrez:
2
5
2022
pubmed:
3
5
2022
medline:
3
5
2022
Statut:
epublish
Résumé
Theory of Mind (ToM)-the ability of the human mind to attribute mental states to others-is a key component of human cognition. In order to understand other people's mental states or viewpoint and to have successful interactions with others within social and occupational environments, this form of social cognition is essential. The same capability of inferring human mental states is a prerequisite for artificial intelligence (AI) to be integrated into society, for example in healthcare and the motoring industry. Autonomous cars will need to be able to infer the mental states of human drivers and pedestrians to predict their behavior. In the literature, there has been an increasing understanding of ToM, specifically with increasing cognitive science studies in children and in individuals with Autism Spectrum Disorder. Similarly, with neuroimaging studies there is now a better understanding of the neural mechanisms that underlie ToM. In addition, new AI algorithms for inferring human mental states have been proposed with more complex applications and better generalisability. In this review, we synthesize the existing understanding of ToM in cognitive and neurosciences and the AI computational models that have been proposed. We focus on preference learning as an area of particular interest and the most recent neurocognitive and computational ToM models. We also discuss the limitations of existing models and hint at potential approaches to allow ToM models to fully express the complexity of the human mind in all its aspects, including values and preferences.
Identifiants
pubmed: 35493614
doi: 10.3389/frai.2022.778852
pmc: PMC9038841
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
778852Informations de copyright
Copyright © 2022 Langley, Cirstea, Cuzzolin and Sahakian.
Déclaration de conflit d'intérêts
FC is the Director of Oxford AI Consulting, and does consultancy for Huawei Canada. BS consults for Cambridge Cognition and Greenfield BioVentures. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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