Autonomous Causally-Driven Explanation of Actions

Garrett Katz, Dale Dullnig, Gregory P. Davis, Rodolphe J. Gentili, James A. Reggia

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

Abstract

We propose a cause-effect reasoning mechanism with which an autonomous system can justify planned actions to a human end user. The mechanism is based on a structure we call a 'causal plan graph,' which encodes the causal relationships between the actions, intentions, and goals of the autonomous system. Causal chains within this graph can potentially serve as intuitive, human-friendly justifications for the autonomous system's planned actions. A prototype of this mechanism is tested in simulation on a set of planning problems from an autonomous maintenance scenario. We demonstrate empirically that shortest path algorithms can effectively reduce a very large number of possible causal chains to a small, intelligible subset that might reasonably be inspected and ranked by a human. Consequently this work can serve as the basis for an experimental platform for future end user studies with human participants.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
EditorsFernando G. Tinetti, Quoc-Nam Tran, Leonidas Deligiannidis, Mary Qu Yang, Mary Qu Yang, Hamid R. Arabnia
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages772-778
Number of pages7
ISBN (Electronic)9781538626528
DOIs
StatePublished - Dec 4 2018
Externally publishedYes
Event2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017 - Las Vegas, United States
Duration: Dec 14 2017Dec 16 2017

Other

Other2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
CountryUnited States
CityLas Vegas
Period12/14/1712/16/17

Keywords

  • cause-effect reasoning
  • explainable artificial intelligence (XAI)
  • imitation learning
  • robotics

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Safety, Risk, Reliability and Quality

Fingerprint Dive into the research topics of 'Autonomous Causally-Driven Explanation of Actions'. Together they form a unique fingerprint.

  • Cite this

    Katz, G., Dullnig, D., Davis, G. P., Gentili, R. J., & Reggia, J. A. (2018). Autonomous Causally-Driven Explanation of Actions. In F. G. Tinetti, Q-N. Tran, L. Deligiannidis, M. Q. Yang, M. Q. Yang, & H. R. Arabnia (Eds.), Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017 (pp. 772-778). [8560892] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSCI.2017.133