2017 IJCAI IJCAI 2017

AToM: An Analogical Theory of Mind

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.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Interdisciplinary
🐣 Hot Topic Early Bird — cognitive modeling
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio

Authors