Advertisement

Argument-Based Plan Explanation

  • Nir OrenEmail author
  • Kees van Deemter
  • Wamberto W. Vasconcelos
Chapter
  • 11 Downloads

Abstract

We describe a tool for providing explanation of plans to non-technical users, built on formal argumentation and dialogue theory, and supported by natural language generation and visualisation technologies. We describe how arguments can be generated from domain rules, and how justified arguments can be identified through dialogue, allowing the system to use such a dialogue to explain a plan. We provide information about our prototype system implementation, discussing its current limitations, and identifying potential avenues for future research.

Notes

Acknowledgements

This work was supported by the Engineering and Physical Sciences Research Council (EPSRC, UK), grant ref. EP/J012084/1 (“Scrutable Autonomous Systems”).

References

  1. 1.
    P. Baroni, M. Caminada, and M. Giacomin. An introduction to argumentation semantics. The Knowledge Engineering Review, 26(4):365–410, 2011.CrossRefGoogle Scholar
  2. 2.
    P. Baroni and M. Giacomin. Semantics of Abstract Argument Systems, pages 25–44. Springer US, Boston, MA, 2009.Google Scholar
  3. 3.
    M. Caminada. A discussion game for grounded semantics. In International Workshop on Theory and Applications of Formal Argumentation, pages 59–73. Springer, 2015.Google Scholar
  4. 4.
    M. Caminada, S. Modgil, and N. Oren. Preferences and unrestricted rebut. In Proceedings of the 2014 conference on Computational Models of Argument, pages 209–220, 2014.Google Scholar
  5. 5.
    M. Caminada and M. Podlaszewski. Grounded semantics as persuasion dialogue. In Proceedings of the 4th International Conference on Computational Models of Argument (COMMA 2012), volume 245, pages 478–485. IOS Press, 2012.Google Scholar
  6. 6.
    F. Cerutti, N. Tintarev, and N. Oren. Formal arguments, preferences and natural language interfaces to humans: an empirical evaluation. In Proc. ECAI, pages 207–212, 2014.Google Scholar
  7. 7.
    M. L. Cobo, D. C. Martínez, and G. R. Simari. On admissibility in timed abstract argumentation frameworks. In ECAI, volume 215, pages 1007–1008, 2010.Google Scholar
  8. 8.
    K. V. Deemter, M. Theune, and E. Krahmer. Real versus template-based natural language generation: A false opposition? Computational Linguistics, 31(1):15–24, 2005.CrossRefGoogle Scholar
  9. 9.
    P. M. Dung. On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence, 77(2):321–357, 1995.MathSciNetCrossRefGoogle Scholar
  10. 10.
    D. R. García, A. J. García, and G. R. Simari. Defeasible reasoning and partial order planning. In Proceedings of the 5th International Conference on Foundations of Information and Knowledge Systems, FoIKS’08, pages 311–328, Berlin, Heidelberg, 2008. Springer-Verlag.Google Scholar
  11. 11.
    A. Gatt and E. Krahmer. Survey of the state of the art in natural language generation: Core tasks, applications and evaluation. Journal of Artificial Intelligence Research, 61:65–170, 2018.MathSciNetCrossRefGoogle Scholar
  12. 12.
    A. Gatt and E. Reiter. SimpleNLG: A realisation engine for practical applications. In Proceedings of the 12th European Workshop on Natural Language Generation (ENLG 2009), pages 90–93, 2009.Google Scholar
  13. 13.
    D. Gunning, Explainable artificial intelligence (XAI). Defense Advanced Research Projects Agency, DARPA/I20, (DARPA, 2017).Google Scholar
  14. 14.
    V. Koeman, L. A. Dennis, M. Webster, M. Fisher, and K. Hindriks. The “Why did you do that?” Button: Answering Why-questions for end users of Robotic Systems. In Proceedings of the 7th International Workshop in Engineering Multi-Agent Systems, Montreal, Canada, 2019.Google Scholar
  15. 15.
    H. Mercier and D. Sperber. The enigma of reason. Harvard University Press, 2017.Google Scholar
  16. 16.
    S. Modgil. Reasoning about preferences in argumentation frameworks. Artificial Intelligence, 173(9–10):901–934, 2009.MathSciNetCrossRefGoogle Scholar
  17. 17.
    S. Modgil and M. Caminada. Proof Theories and Algorithms for Abstract Argumentation Frameworks, chapter 6. Springer, 2009.Google Scholar
  18. 18.
    S. Modgil and H. Prakken. The ASPIC+  framework for structured argumentation: a tutorial. Argument and Computation, 5(1):31–62, 2014.CrossRefGoogle Scholar
  19. 19.
    S. Pajares and E. Onaindia. Temporal defeasible argumentation in multi-agent planning. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence - Volume Three, IJCAI’11, pages 2834–2835. AAAI Press, 2011.Google Scholar
  20. 20.
    P. Pardo, S. Pajares, E. Onaindia, L. Godo, and P. Dellunde. Multiagent argumentation for cooperative planning in DeLP-POP. In The 10th International Conference on Autonomous Agents and Multiagent Systems-Volume 3, pages 971–978. International Foundation for Autonomous Agents and Multiagent Systems, 2011.Google Scholar
  21. 21.
    H. Prakken. Combining sceptical epistemic reasoning with credulous practical reasoning. COMMA, 144:311–322, 2006.MathSciNetGoogle Scholar
  22. 22.
    I. Rahwan, I. Madakkatel, M., J. Bonnefon, R. N. Awan, and S. Abdallah. Behavioral experiments for assessing the abstract argumentation semantics of reinstatement. Cognitive Science, 34(8):1483–1502, 2010.Google Scholar
  23. 23.
    E. Reiter and R. Dale. Building applied natural language generation systems. Natural Language Engineering, 3(1):57–87, 1997.CrossRefGoogle Scholar
  24. 24.
    Z. Shams and N. Oren. A two-phase dialogue game for skeptical preferred semantics. In JELIA, volume 10021 of Lecture Notes in Computer Science, pages 570–576, 2016.Google Scholar
  25. 25.
    N. Tintarev, R. Kutlak, J. Masthoff, K. Van Deemter, N. Oren, and W. W. Vasconcelos. Adaptive visualization of plans. In UMAP Workshops, 2014.Google Scholar
  26. 26.
    N. Tintarev and J. Masthoff. Effects of individual differences in working memory on plan presentational choices. Frontiers in Psychology, 7:1793, 2016.CrossRefGoogle Scholar
  27. 27.
    M. Winikoff. Debugging agent programs with why? Questions. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, pages 251–259. International Foundation for Autonomous Agents and Multiagent Systems, 2017.Google Scholar
  28. 28.
    Y. Wu, M. Caminada, and M. Podlaszewski. A labelling-based justification status of arguments. Studies in Logic, 3(4):12–29, 2010.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Nir Oren
    • 1
    Email author
  • Kees van Deemter
    • 2
  • Wamberto W. Vasconcelos
    • 1
  1. 1.Computing ScienceUniversity of AberdeenAberdeenUK
  2. 2.Information & Computing SciencesUniversity of UtrechtUtrechtThe Netherlands

Personalised recommendations