Understanding Intention for Machine Theory of Mind: a Position Paper

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Theory of Mind is often characterized as the ability to recognize desires, beliefs, and intentions of others. In this position paper, I look at the literature on modeling Theory of Mind in machines and find that, to date, intention is not usually a focus. I define what I mean by intention-choice with commitment-following prior work. Intention has a long history of research in some communities, and I offer one theoretical framework for modeling intention as a starting point. I take inspiration from how children learn intention through joint attention with others and how that leads to Theory of Mind. I argue that though models of machine Theory of Mind need not follow the same learning progression as children, intention is an aspect of Theory of Mind that should be more explicit.

Original languageEnglish
Title of host publicationRO-MAN 2022 - 31st IEEE International Conference on Robot and Human Interactive Communication
Subtitle of host publicationSocial, Asocial, and Antisocial Robots
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages450-453
Number of pages4
ISBN (Electronic)9781728188591
DOIs
StatePublished - 2022
Event31st IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2022 - Napoli, Italy
Duration: 29 Aug 20222 Sep 2022

Publication series

NameRO-MAN 2022 - 31st IEEE International Conference on Robot and Human Interactive Communication: Social, Asocial, and Antisocial Robots

Conference

Conference31st IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2022
Country/TerritoryItaly
CityNapoli
Period29/08/222/09/22

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