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Abstract

Conflict resolution is an important issue. Dung’s preferred semantics is a promising approach to resolving conflicts. However, such semantics is not capable of dealing with conflicts satisfactorily in the argumentation frameworks wherein there exists only empty admissible set. To enhance Dung’s preferred semantics, we propose a novel semantics which follows the philosophy of Dung’s preferred semantics, while satisfactorily resolving conflicts among arguments. In order to define our semantics, we first redefine Dung’s basic notion acceptability by using pairs of sets of arguments and then propose the admissible semantics based on such notion. Relationships with Dung’s preferred semantics, ideal semantics and semi-stable semantics are analyzed, and comparisons with other approaches such as CF2 semantics are also discussed.

Keywords

argumentation extensions preferred semantics conflict resolution 

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References

  1. 1.
    Dung, P.M.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77(2), 321–358 (1995)CrossRefMATHMathSciNetGoogle Scholar
  2. 2.
    Elvang-Gøransson, M., Hunter, A.: Argumentative logics: Reasoning with classically inconsistent information. Data Knowledge Engineering 16(2), 125–145 (1995)CrossRefGoogle Scholar
  3. 3.
    Modgil, S.: Reasoning about preferences in argumentation frameworks. Artificial Intelligence 173(9-10), 901–934 (2009)CrossRefMATHMathSciNetGoogle Scholar
  4. 4.
    Pollock, J.L.: How to reason defeasibly. Artificial Intelligence 57(1), 1–42 (1992)CrossRefMATHMathSciNetGoogle Scholar
  5. 5.
    Prakken, H., Sartor, G.: Argument-based extended logic programming with defeasible priorities. Journal of Applied Non-Classical Logics 7(1), 25–75 (1997)CrossRefMATHMathSciNetGoogle Scholar
  6. 6.
    Vreeswijk, G.: Abstract argumentation systems. Artificial Intelligence 90(1-2), 225–279 (1997)CrossRefMATHMathSciNetGoogle Scholar
  7. 7.
    Amgoud, L., Cayrol, C.: Inferring from inconsistency in preference-based argumentation frameworks. Journal of Automated Reasoning 29(2), 125–169 (2002)CrossRefMATHMathSciNetGoogle Scholar
  8. 8.
    Baroni, P., Giacomin, M.: Solving semantic problems with odd-length cycles in argumentation. In: Nielsen, T.D., Zhang, N.L. (eds.) ECSQARU 2003. LNCS (LNAI), vol. 2711, pp. 440–451. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  9. 9.
    Baroni, P., Giacomin, M., Guida, G.: Scc-recursiveness: a general schema for argumentation semantics. Artificial Intelligence 168(1-2), 162–210 (2005)CrossRefMATHMathSciNetGoogle Scholar
  10. 10.
    Bench-Capon, T.J.M., Dunne, P.E.: Argumentation in artificial intelligence. Artificial Intelligence 171(10-15), 619–641 (2007)CrossRefMATHMathSciNetGoogle Scholar
  11. 11.
    Caminada, M.: Contamination in formal argumentation systems. In: Verbeeck, K., Tuyls, K., Nowé, A., Manderick, B., Kuijpers, B. (eds.) Proceedings of the 17th Belgium-Netherlands Conference on Artificial Intelligence 2005, pp. 59–65. Koninklijke Vlaamse Academie van Belie voor Wetenschappen en Kunsten, Brussels (2005)Google Scholar
  12. 12.
    Nieves, J.C., Cortés, U., Osorio, M., Olmos, I., Gonzalez, J.A.: Defining new argumentation-based semantics by minimal models. In: 7th Mexican International Conference on Computer Science, pp. 210–220. IEEE Computer Society, Los Alamitos (2006)Google Scholar
  13. 13.
    Prakken, H., Vreeswijk, G.: Logics for defeasible argumentation. In: Handbook of Philosophical Logic, 2nd edn. Kluwer Academic, Dordrecht (2002)Google Scholar
  14. 14.
    Dung, P.M., Mancarella, P., Toni, F.: A dialectic procedure for sceptical, assumption-based argumentation. In: Dunne, P.E., Bench-Capon, T.J.M. (eds.) COMMA 2006. Frontiers in Artificial Intelligence and Applications, vol. 144, pp. 145–156. IOS Press, Amsterdam (2006)Google Scholar
  15. 15.
    Caminada, M.: Semi-stable semantics. In: Dunne, P.E., Bench-Capon, T.J.M. (eds.) COMMA 2006. Frontiers in Artificial Intelligence and Applications, vol. 144, pp. 121–130. IOS Press, Amsterdam (2006)Google Scholar
  16. 16.
    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)CrossRefMATHMathSciNetGoogle Scholar
  17. 17.
    Dunne, P.E., Bench-Capon, T.J.M.: Complexity and Combinatorial Properties of Argument Systems. Technical report, University of Liverpool, Department of Computer Science (2001)Google Scholar
  18. 18.
    Dunne, P.E., Bench-Capon, T.J.M.: Coherence in finite argument systems. Artificial Intelligence 141(1/2), 187–203 (2002)CrossRefMATHMathSciNetGoogle Scholar
  19. 19.
    Doutre, S., Mengin, J.: Preferred extensions of argumentation frameworks: Query answering and computation. In: Goré, R.P., Leitsch, A., Nipkow, T. (eds.) IJCAR 2001. LNCS (LNAI), vol. 2083, pp. 272–288. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  20. 20.
    Cayrol, C., Doutre, S., Mengin, J.: On decision problems related to the preferred semantics for argumentation frameworks. Journal of Logic and Computation 13(3), 377–403 (2003)CrossRefMATHMathSciNetGoogle Scholar
  21. 21.
    Dung, P.M., Mancarella, P., Toni, F.: Computing ideal sceptical argumentation. Artificial Intelligence 171(10-15), 642–674 (2007)CrossRefMATHMathSciNetGoogle Scholar
  22. 22.
    Nieves, J.C., Cortés, U., Osorio, M.: Preferred extensions as stable models. Theory and Practice of Logic Programming 8(4), 527–543 (2008)CrossRefMATHMathSciNetGoogle Scholar
  23. 23.
    Baroni, P., Giacomin, M.: Resolution-based argumentation semantics. In: Besnard, P., Doutre, S., Hunter, A. (eds.) COMMA 2008. Frontiers in Artificial Intelligence and Applications, vol. 172, pp. 25–36. IOS Press, Amsterdam (2008)Google Scholar
  24. 24.
    Marquis, S.C., Devred, C., Marquis, P.: Prudent semantics for argumentation frameworks. In: 17th International Conference on Tools with Artificial Intelligence, pp. 568–572. IEEE Computer Society, Los Alamitos (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Zhihu Zhang
    • 1
  • Zuoquan Lin
    • 1
  1. 1.School of Mathematical SciencesPeking UniversityBeijingChina

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