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Robot causal discovery aided by human interaction
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.ORCID iD: 0009-0001-3326-2643
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0001-7242-2200
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.ORCID iD: 0000-0003-3187-1987
2023 (English)In: 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), IEEE, 2023, p. 1731-1736Conference paper, Published paper (Refereed)
Abstract [en]

Causality is relatively unexplored in robotics even if it is highly relevant, in several respects. In this paper, we study how a robot’s causal understanding can be improved by allowing the robot to ask humans causal questions. We propose a general algorithm for selecting direct causal effects to ask about, given a partial causal representation (using partially directed acyclic graphs, PDAGs) obtained from observational data. We propose three versions of the algorithm inspired by different causal discovery techniques, such as constraint-based, score-based, and interventions. We evaluate the versions in a simulation study and our results show that asking causal questions improves the causal representation over all simulated scenarios. Further, the results show that asking causal questions based on PDAGs discovered from data provides a significant improvement compared to asking questions at random, and the version inspired by score-based techniques performs particularly well over all simulated experiments.

Place, publisher, year, edition, pages
IEEE, 2023. p. 1731-1736
Series
IEEE RO-MAN proceedings, ISSN 1944-9445, E-ISSN 1944-9437
Keywords [en]
human-robot-interaction (hri), causal discovery, causal inference
National Category
Robotics Computer Sciences Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:umu:diva-219029DOI: 10.1109/RO-MAN57019.2023.10309376ISI: 001108678600221Scopus ID: 2-s2.0-85187012918ISBN: 9798350336702 (electronic)ISBN: 9798350336719 (print)OAI: oai:DiVA.org:umu-219029DiVA, id: diva2:1824543
Conference
IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), Busan, Korea, August 28-31, 2023
Funder
Swedish Research CouncilAvailable from: 2024-01-05 Created: 2024-01-05 Last updated: 2024-03-18Bibliographically approved

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Edström, FilipHellström, Thomasde Luna, Xavier

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
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Output format
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