ML Anthology

AToM: An Analogical Theory of Mind

Irina Rabkina
IJCAI 2017 pp. 5203-5204
doi:10.24963/IJCAI.2017/761 /ijcai/2017/rabkina2017ijcai-atom/

Abstract

Theory of Mind (ToM) has been well studied in psychology. It is what gives adults the ability to predict other people’s beliefs, desires, and related actions. When ToM is not yet developed, as in young children, social interaction is difficult. A cognitive system that interacts with humans on a regular basis would benefit from having a ToM. In this extended abstract, I propose a computational model of ToM, Analogical Theory of Mind (AToM), based on Bach’s [2012, 2014] theoretical Structure-Mapping model of ToM. Completed work demonstrates the plausibility of AToM. Future steps include a full implementation and test of AToM.

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Cite

Text

Rabkina. "AToM: An Analogical Theory of Mind." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/761

Markdown

[Rabkina. "AToM: An Analogical Theory of Mind." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/rabkina2017ijcai-atom/) doi:10.24963/IJCAI.2017/761

BibTeX

@inproceedings{rabkina2017ijcai-atom,
  title     = {{AToM: An Analogical Theory of Mind}},
  author    = {Rabkina, Irina},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2017},
  pages     = {5203-5204},
  doi       = {10.24963/IJCAI.2017/761},
  url       = {https://mlanthology.org/ijcai/2017/rabkina2017ijcai-atom/}
}