Towards Understanding User Preferences for Explanation Types in Model Reconciliation

Zahra Zahedi, Alberto Olmo, Tathagata Chakraborti, Sarath Sreedharan, Subbarao Kambhampati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Recent work has formalized the explanation process in the context of automated planning as one of model reconciliation - i.e. a process by which the planning agent can bring the explainee's (possibly faulty) model of a planning problem closer to its understanding of the ground truth until both agree that its plan is the best possible. The content of explanations can thus range from misunderstandings about the agent's beliefs (state), desires (goals) and capabilities (action model). Though existing literature has considered different kinds of these model differences to be equivalent, literature on the explanations in social sciences has suggested that explanations with similar logical properties may often be perceived differently by humans. In this brief report, we explore to what extent humans attribute importance to different kinds of model differences that have been traditionally considered equivalent in the model reconciliation setting. Our results suggest that people prefer the explanations which are related to the effects of actions.

Original languageEnglish (US)
Title of host publicationHRI 2019 - 14th ACM/IEEE International Conference on Human-Robot Interaction
PublisherIEEE Computer Society
Pages648-649
Number of pages2
ISBN (Electronic)9781538685556
DOIs
StatePublished - Mar 22 2019
Event14th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2019 - Daegu, Korea, Republic of
Duration: Mar 11 2019Mar 14 2019

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
Volume2019-March
ISSN (Electronic)2167-2148

Conference

Conference14th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2019
CountryKorea, Republic of
CityDaegu
Period3/11/193/14/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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    Zahedi, Z., Olmo, A., Chakraborti, T., Sreedharan, S., & Kambhampati, S. (2019). Towards Understanding User Preferences for Explanation Types in Model Reconciliation. In HRI 2019 - 14th ACM/IEEE International Conference on Human-Robot Interaction (pp. 648-649). [8673097] (ACM/IEEE International Conference on Human-Robot Interaction; Vol. 2019-March). IEEE Computer Society. https://doi.org/10.1109/HRI.2019.8673097