Supporting Argumentation Systems by Graph Representation and Computation

  • Jérôme Fortin
  • Rallou Thomopoulos
  • Jean-Rémi Bourguet
  • Marie-Laure Mugnier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7205)


Argumentation is a reasoning model based on arguments and on attacks between arguments. It consists in evaluating the acceptability of arguments, according to a given semantics. Due to its generality, Dung’s framework for abstract argumentation systems, proposed in 1995, is a reference in the domain. Argumentation systems are commonly represented by graph structures, where nodes and edges respectively represent arguments and attacks between arguments. However beyond this graphical support, graph operations have not been considered as reasoning tools in argumentation systems. This paper proposes a conceptual graph representation of an argumentation system and a computation of argument acceptability relying on conceptual graph default rules.


Argumentation Framework Default Theory Conceptual Graph Nonmonotonic Reasoning Concept Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
  2. 2.
    Baget, J.-F., Croitoru, M., Fortin, J., Thomopoulos, R.: Default Conceptual Graph Rules: Preliminary Results for an Agronomy Application. In: Rudolph, S., Dau, F., Kuznetsov, S.O. (eds.) ICCS 2009. LNCS(LNAI), vol. 5662, pp. 86–99. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  3. 3.
    Baget, J.-F., Fortin, J.: Default Conceptual Graph Rules, Atomic Negation and Tic-Tac-Toe. In: Croitoru, M., Ferré, S., Lukose, D. (eds.) ICCS 2010. LNCS, vol. 6208, pp. 42–55. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Bentahar, J., Moulin, B., Bélanger, M.: A taxonomy of argumentation models used for knowledge representation. Artif. Intell. Rev. 33(3), 211–259 (2010)CrossRefGoogle Scholar
  5. 5.
    Bondarenko, A., Dung, P.M., Kowalski, R.A., Toni, F.: An abstract, argumentation-theoretic approach to default reasoning. Artificial Intelligence Journal 93, 63–101 (1997)MathSciNetzbMATHCrossRefGoogle Scholar
  6. 6.
    Bourguet, J.R.: Contribution aux méthodes d’argumentation pour la prise de décision. Application à l´arbitrage au sein de la filière céréalière. Ph.D. thesis, Université Montpellier II (2010)Google Scholar
  7. 7.
    Brewka, G., Eiter, T.: Prioritizing default logic: Abridged report. In: Festschrift on the Occasion of Prof. Dr. W. Bibel’s 60th Birthday. Kluwer (1999)Google Scholar
  8. 8.
    Carneades: (website),
  9. 9.
    Chein, M., Mugnier, M.L., Simonet, G.: Nested Graphs: A Graph-based Knowledge Representation Model with FOL Semantics. In: Proc. of KR 1998, pp. 524–534. Morgan Kaufmann (1998)Google Scholar
  10. 10.
    Chein, M., Mugnier, M.L.: Graph-based Knowledge Representation and Reasoning. Computational Foundations of Conceptual Graphs. Advanced Information and Knowledge Processing. Springer, London (2009)Google Scholar
  11. 11.
    Dung, P.M.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence Journal 77, 321–357 (1995)MathSciNetzbMATHCrossRefGoogle Scholar
  12. 12.
    Brewka, G., Niemelä, I., Truszczynski, M.: Nonmonotonic reasoning. In: Lifschitz, V., Porter, B., van Harmelen, F. (eds.) Handbook of Knowledge Representation, pp. 239–284. Elsevier (2007)Google Scholar
  13. 13.
    de Moor, A., Park, J., Croitoru, M.: Argumentation Map Generation with Conceptual Graphs: the Case for ESSENCE. In: Proc. of the 4th ICCS Conceptual Structures Tool Interoperability Workshop (CS-TIW 2009), Russia, pp. 58–69 (2009)Google Scholar
  14. 14.
    Reiter, R.: A logic for default reasoning. Artificial Intelligence 13, 81–132 (1980)MathSciNetzbMATHCrossRefGoogle Scholar
  15. 15.
    Salvat, E., Mugnier, M.L.: Sound and Complete Forward and Backward Chaining of Graph Rules. In: Eklund, P., Mann, G.A., Ellis, G. (eds.) ICCS 1996. LNCS, vol. 1115, pp. 248–262. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  16. 16.
    Sowa, J.F.: Conceptual Structures: Information Proc. in Mind and Machine. Addison–Wesley (1984)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jérôme Fortin
    • 1
  • Rallou Thomopoulos
    • 2
  • Jean-Rémi Bourguet
    • 3
  • Marie-Laure Mugnier
    • 1
  1. 1.Université Montpellier IIMontpellier cedex 5France
  2. 2.INRA/IATEMontpellierFrance
  3. 3.Université Montpellier IIIMontpellierFrance

Personalised recommendations