Preference-Based Argumentation Handling Dynamic Preferences Built on Prioritized Logic Programming

  • Toshiko Wakaki
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7047)


To treat dynamic preferences correctly is crucially required in the fields of argumentation as well as nonmonotonic reasoning. To meet such requirements, first, we propose a hierarchical Prioritized Logic Program (or a hierarchical PLP, for short), which enhances the formalism of Sakama and Inoue’s PLP so that it can represent and reason about dynamic preferences. Second, using such a hierarchical PLP as the underlying language, the proposed method defines the preference-based argumentation framework (called the dynamic PAF) built from it. This enables us to argue and reason about dynamic preferences in argumentation. Finally we show the interesting relationship between semantics of a hierarchical PLP given by preferred answer sets and semantics of the dynamic PAF given by \({\cal P}\)-extensions.


Logic Program Logic Programming Argumentation Framework Nonmonotonic Reasoning Strict Partial Order 
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  1. 1.
    Amgoud, L., Cayrol, C.: A reasoning model based on the production of acceptable arguments. Annals of Mathematics and Artificial Intelligence 34(1-3), 197–215 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    Amgoud, L., Vesic, S.: Repairing preference-based argumentation frameworks. In: Proceedings of IJCAI 2009, pp. 665–670 (2009)Google Scholar
  3. 3.
    Brewka, G.: Well-founded Semantics for Extended Logic Programs with Dynamic Preferences. Journal of Artificial Intelligence Research 4, 19–36 (1996)MathSciNetzbMATHGoogle Scholar
  4. 4.
    Brewka, G., Eiter, T.: Preferred answer sets for extended logic programs. Artificial Intelligence 109, 297–356 (1999)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Eiter, T., Faber, W., Leone, N., Pfeifer, G.: Computing preferred answer sets by meta-interpretation in answer set programming. Theory and Practice of Logic Programming 3(4-5), 463–498 (2003)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Caminada, M., Amgoud, L.: On the evaluation of argumentation formalisms. Artificial Intelligence 171(5-6), 286–310 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Delgrande, J.P., Schaub, T., Tompits, H.: A framework for compiling preferences in logic programs. Theory and Practice of Logic Programming 3(2), 129–187 (2003)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Delgrande, J.P., Schaub, T., Tompits, H., Wang, K.: A Classification and survey of preference handling approaches in nonmonotonic reasoning. Computational Intelligence 20(2), 308–334 (2004)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Dung, P.M.: An argumentation semantics for logic programming with explicit negation. In: Proceedings of the Tenth International Conference on Logic programming (ICLP 1993), pp. 616–630. MIT press (1993)Google Scholar
  10. 10.
    Dung, P.M.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming, and n-person games. Artificial Intelligence 77, 321–357 (1995)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Gelfond, M., Lifschitz, V.: The stable model semantics for logic programming. In: Proceedings of the Fifth International Conference and Symposium on Logic Programming (ICLP/SLP-1988), pp. 1070–1080. MIT Press (1988)Google Scholar
  12. 12.
    Gelfond, M., Lifschitz, V.: Classical negation in logic programs and disjunctive databases. New Generation Computing 9, 365–385 (1991)CrossRefzbMATHGoogle Scholar
  13. 13.
    Gordon, T.F.: The pleadings game: An Artificial Intelligence Model of Procedural Justice, Ph.D. thesis, TU Darmstadt (1993)Google Scholar
  14. 14.
    Modgil, S.: Reasoning about preferences in argumentation frameworks. Artificial Intelligence 173, 901–934 (2009)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Modgil, S., Prakken, H.: Reasoning about preferences in Structured Extended Argumentation Frameworks. In: Proceedings of COMMA 2010, pp. 347–358. IOS (2010)Google Scholar
  16. 16.
    Prakken, H., Sartor, G.: Argument-based extended logic programming with defeasible priorities. Journal of Applied Non-Classical Logics 7(1), 25–75 (1997)MathSciNetCrossRefzbMATHGoogle Scholar
  17. 17.
    Schweimeier, R., Schroeder, M.: A Parameterized hierarchy of argumentation semantics for extended logic programming and its application to the well-founded semantics. Theory and Practice of Logic Programming 5(1,2), 207–242 (2005)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Sakama, C., Inoue, K.: Prioritized logic programming and its application to commonsense reasoning. Artificial Intelligence 123, 185–222 (2000)MathSciNetCrossRefzbMATHGoogle Scholar
  19. 19.
    Wakaki, T.: Preference-Based Argumentation Capturing Prioritized Logic Programming. In: McBurney, P. (ed.) ArgMAS 2010. LNCS (LNAI), vol. 6614, pp. 306–325. Springer, Heidelberg (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Toshiko Wakaki
    • 1
  1. 1.Shibaura Institute of TechnologySaitama-cityJapan

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