Uncertainty-Resolving Questions for Social Robots

Minjung Shin, Minsu Jang, Miyoung Cho, Jeh Kwang Ryu

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

1 Scopus citations

Abstract

Social robots should deal with uncertainties in unseen environments and situations in an interactive setting. For humans, questionanswering is one of the most typical activities for resolving or reducing uncertainty by acquiring additional information, which is also desirable for social robots. In this study, we propose a framework for leveraging the research on learning-by-asking techniques for social robots. This framework is inspired by human inquiries. Information seeking by asking should be considered at the multi-dimensional level, including required knowledge, cognitive processes, and question types. These dimensions offer a framework to embed generated questions into the three-dimensional question space, which is expected to provide a reasonable benchmark for the active learning approach and evaluation methodologies of uncertainty-resolving question generation for social robots.

Original languageEnglish
Title of host publicationHRI 2023 - Companion of the ACM/IEEE International Conference on Human-Robot Interaction
PublisherIEEE Computer Society
Pages226-230
Number of pages5
ISBN (Electronic)9781450399708
DOIs
StatePublished - 13 Mar 2023
Event18th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2023 - Stockholm, Sweden
Duration: 13 Mar 202316 Mar 2023

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
ISSN (Electronic)2167-2148

Conference

Conference18th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2023
Country/TerritorySweden
CityStockholm
Period13/03/2316/03/23

Keywords

  • Inquiry type
  • Question generation
  • Question space
  • Social robot
  • Uncertainty resolution

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