Bootstrapping from Language in the Analogical Theory of Mind Model
- Irina Rabkina, Qualitative Reasoning Group, Northwestern University, Evanston, Illinois, United States
- Clifton McFate, EECS, Northwestern University, Evanston, Illinois, United States
- Ken Forbus, Northwestern University, Evanston, Illinois, United States
AbstractMany 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.
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