Abstract
Many psychologists have argued that language acquisition plays an important role in the development of Theory of Mind (ToM) reasoning in children. Several accounts of this interaction exist: some believe that language gives children the ability to express already formed ToM reasoning (e.g. He, Bolz, & Baillargeon, 2011), while others argue that learning specific grammatical structures engenders new reasoning abilities (e.g. de Villiers & Pyers, 1997). Questions remain about the mechanism by which this interaction occurs. In this paper, we show that the Analogical Theory of Mind (AToM; Rabkina et al., 2017) computational model can bootstrap aspects of ToM reasoning from sentential complement training, and that its performance matches improvement patterns of children who are trained using similar stimuli. This provides an implemented algorithmic account of bootstrapping ToM reasoning from language within a broader model of ToM development.
Original language | English (US) |
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Title of host publication | Proceedings of the 40th Annual Meeting of the Cognitive Science Society, CogSci 2018 |
Publisher | The Cognitive Science Society |
Pages | 924-929 |
Number of pages | 6 |
ISBN (Electronic) | 9780991196784 |
State | Published - 2018 |
Event | 40th Annual Meeting of the Cognitive Science Society: Changing Minds, CogSci 2018 - Madison, United States Duration: Jul 25 2018 → Jul 28 2018 |
Publication series
Name | Proceedings of the 40th Annual Meeting of the Cognitive Science Society, CogSci 2018 |
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Conference
Conference | 40th Annual Meeting of the Cognitive Science Society: Changing Minds, CogSci 2018 |
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Country/Territory | United States |
City | Madison |
Period | 7/25/18 → 7/28/18 |
Funding
We thank Dedre Gentner for helpful comments. This research was supported by the Socio-Cognitive Architectures for Adaptable Autonomous Systems Program of the Office of Naval Research, N00014-13-1-0470.
Keywords
- analogy
- cognitive modeling
- false belief
- sentential complements
- structure-mapping
- theory of mind
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Human-Computer Interaction
- Cognitive Neuroscience