Bootstrapping from Language in the Analogical Theory of Mind Model

Irina Rabkina, Clifton McFate, Kenneth D. Forbus

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

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 languageEnglish (US)
Title of host publicationProceedings of the 40th Annual Meeting of the Cognitive Science Society, CogSci 2018
PublisherThe Cognitive Science Society
Pages924-929
Number of pages6
ISBN (Electronic)9780991196784
StatePublished - 2018
Event40th Annual Meeting of the Cognitive Science Society: Changing Minds, CogSci 2018 - Madison, United States
Duration: Jul 25 2018Jul 28 2018

Publication series

NameProceedings of the 40th Annual Meeting of the Cognitive Science Society, CogSci 2018

Conference

Conference40th Annual Meeting of the Cognitive Science Society: Changing Minds, CogSci 2018
Country/TerritoryUnited States
CityMadison
Period7/25/187/28/18

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

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