Implementing Theory of Mind on a Robot Using Dynamic Epistemic Logic

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Abstract

Previous research has claimed dynamic epistemic logic (DEL) to be a suitable formalism for representing essential aspects of a Theory of Mind (ToM) for an autonomous agent. This includes the ability of the formalism to represent the reasoning involved in false-belief tasks of arbitrary order, and hence for autonomous agents based on the formalism to become able to pass such tests. This paper provides evidence for the claims by documenting the implementation of a DEL-based reasoning system on a humanoid robot. Our implementation allows the robot to perform cognitive perspective-taking, in particular to reason about the first- and higherorder beliefs of other agents. We demonstrate how this allows the robot to pass a quite general class of false-belief tasks involving human agents. Additionally, as is briefly illustrated, it allows the robot to proactively provide human agents with relevant information in situations where a system without ToM-abilities would fail. The symbolic grounding problem of turning robotic sensor input into logical action descriptions in DEL is achieved via a perception system based on deep neural networks.
Original languageEnglish
Title of host publicationProceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
PublisherInternational Joint Conference on Artificial Intelligence Organization
Publication date2020
Pages1615-1621
ISBN (Print)978-0-9992411-6-5
DOIs
Publication statusPublished - 2020
EventTwenty-Ninth International Joint Conference on Artificial Intelligence - Scheduled for July 2020, postponed due to the Corona pandemic, Yokohama, Japan
Duration: 7 Jan 202115 Jan 2021
https://ijcai20.org/

Conference

ConferenceTwenty-Ninth International Joint Conference on Artificial Intelligence
LocationScheduled for July 2020, postponed due to the Corona pandemic
Country/TerritoryJapan
CityYokohama
Period07/01/202115/01/2021
Internet address

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