Advertisement

On a Formal Treatment of Deception in Argumentative Dialogues

  • Kazuko TakahashiEmail author
  • Shizuka Yokohama
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10207)

Abstract

This paper formalizes a dialogue that includes dishonest arguments in persuasion. We propose a dialogue model that uses a predicted opponent model and define a protocol using this prediction with an abstract argumentation framework. We focus on deception as dishonesty; that is, the case in which an agent hides her knowledge. We define the concepts of dishonest argument and suspicious argument by means of the acceptance of arguments in this model. We show how a dialogue including dishonest arguments proceeds according to the protocol and discuss a condition for a dishonest argument to be accepted without being revealed.

Keywords

Argumentation Dialogue Persuasion Dishonesty Opponent model 

References

  1. 1.
    Amgoud, L., Maudet, N., Parsons, S.: Modeling dialogues using argumentation. In: ICMAS2000, pp. 31–38 (2000)Google Scholar
  2. 2.
    Amgoud, L., de Saint-Cyr, F.D.: An axiomatic approach for persuasion dialogs. In: ICTAI 2013, pp. 618–625 (2013)Google Scholar
  3. 3.
    Bench-Capon, T.: Persuasion in practice argument using value-based argumentation frameworks. J. Log. Comput. 13(3), 429–448 (2003)MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Baroni, P., Caminada, M., Giacomin, G.: An introduction to argumentation semantics. Knowl. Eng. Rev. 26(4), 365–410 (2011)CrossRefGoogle Scholar
  5. 5.
    Black, E., Hunter, A.: Reasons and options for updating an opponent model in persuasion dialogues. In: Black, E., Modgil, S., Oren, N. (eds.) TAFA 2015. LNCS (LNAI), vol. 9524, pp. 21–39. Springer, Cham (2015). doi: 10.1007/978-3-319-28460-6_2 CrossRefGoogle Scholar
  6. 6.
    Caminada, M.: Truth, Lies and Bullshit; distinguishing classes of dishonesty. IJCAI Workshop on Social, Simulation, pp. 39–50 (2009)Google Scholar
  7. 7.
    Dung, P.M.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artif. Intell. 77, 321–357 (1995)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Hadjinikolis, C., Siantos, Y., Modgil, S., Black, E., McBurney, P.: Opponent modelling in persuasion dialogues. In: IJCAI 2013, pp. 164–170 (2013)Google Scholar
  9. 9.
    Prakken, H.: Formal systems for persuasion dialogue. Knowl. Eng. Rev. 21(2), 163–188 (2006)CrossRefGoogle Scholar
  10. 10.
    Prakken, H., Reed, C., Walton, D.: Dialogues about the burden of proof. In: ICAIL 2005, pp. 115–124 (2005)Google Scholar
  11. 11.
    Rahwan, I., Simari, G. (eds.): Argumentation in Artificial Intelligence. Springer, Heidelberg (2009)Google Scholar
  12. 12.
    Rahwan, I., Lason, K., Tohmé, F.: A characterization of strategy-proofness for grounded argumentation semantics. In: IJCAI 2009, pp. 251–256 (2009)Google Scholar
  13. 13.
    Rienstra, T., Thimm, M., Oren, N.: Opponent models with uncertainty for strategic argumentation. In: IJCAI 2013, pp. 332–338 (2013)Google Scholar
  14. 14.
    Sakama, C.: Dishonest arguments in debate games. COMMA 2012, pp. 177–184 (2012)Google Scholar
  15. 15.
    Sakama, C., Caminada, M., Herzig, A.: A formal account of dishonesty. Log. J. IGPL 23(2), 259–294 (2015)MathSciNetCrossRefGoogle Scholar
  16. 16.
    Thimm, M., García, A.J.: On strategic argument selection in structured argumentation systems. In: McBurney, P., Rahwan, I., Parsons, S. (eds.) ArgMAS 2010. LNCS (LNAI), vol. 6614, pp. 286–305. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-21940-5_17 CrossRefGoogle Scholar
  17. 17.
    Yokohama, S., Takahashi, K.: What should an agent know not to fail in persuasion? In: Rovatsos, M., Vouros, G., Julian, V. (eds.) EUMAS/AT -2015. LNCS (LNAI), vol. 9571, pp. 219–233. Springer, Cham (2016). doi: 10.1007/978-3-319-33509-4_18 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Science and TechnologyKwansei Gakuin UniversitySandaJapan

Personalised recommendations