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Communicating Safety of Planned Paths via Optimally-Simple Explanations

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KI 2022: Advances in Artificial Intelligence (KI 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13404))

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Abstract

Artificial intelligence is often used in path-planning contexts. Towards improved methods of explainable AI for planned paths, we seek optimally simple explanations to guarantee path safety for a planned route over roads. We present a two-dimensional discrete domain, analogous to a road map, which contains a set of obstacles to be avoided. Given a safe path and constraints on the obstacle locations, we propose a family of specially-defined constraint sets, named explanatory hulls, into which all obstacles may be grouped. We then show that an optimal grouping of the obstacles into such hulls will achieve the absolute minimum number of constraints necessary to guarantee no obstacle-path intersection. From an approximation of this minimal set, we generate a natural-language explanation which communicates path safety in a minimum number of explanatory statements.

This work was supported in part by the United States Department of Defense (DoD) through the National Defense Science and Engineering Graduate (NDSEG) Fellowship Program.

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Notes

  1. 1.

    https://github.com/n-brindise/plan_expl.

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Authors and Affiliations

  1. University of Illinois Urbana-Champaign, 104 S Wright St., Urbana, IL, 61801, USA

    Noel Brindise & Cedric Langbort

Authors
  1. Noel Brindise
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  2. Cedric Langbort
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Corresponding author

Correspondence to Noel Brindise .

Editor information

Editors and Affiliations

  1. University of Trier, Trier, Rheinland-Pfalz, Germany

    Ralph Bergmann

  2. University of Trier, Trier, Germany

    Lukas Malburg

  3. University of Trier, Trier, Germany

    Stephanie C. Rodermund

  4. University of Trier, Trier, Germany

    Ingo J. Timm

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Brindise, N., Langbort, C. (2022). Communicating Safety of Planned Paths via Optimally-Simple Explanations. In: Bergmann, R., Malburg, L., Rodermund, S.C., Timm, I.J. (eds) KI 2022: Advances in Artificial Intelligence. KI 2022. Lecture Notes in Computer Science(), vol 13404. Springer, Cham. https://doi.org/10.1007/978-3-031-15791-2_4

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  • DOI: https://doi.org/10.1007/978-3-031-15791-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-15790-5

  • Online ISBN: 978-3-031-15791-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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