Abstract
Argumentation theory is a reasoning process based on constructing arguments, determining conflicts between arguments and determining acceptable arguments. Dung’s argumentation framework is an abstract framework based on a set of arguments and a binary defeat relation defined over the set [12]. The output of an argumentation framework is a multi-set of acceptable arguments called acceptable extensions. An extension is a set of arguments which can be used together in order to support a decision, a viewpoint, etc. Thus, it should satisfy two basic requirements: (1) an extension is conflict-free, i.e., no defeat relation holds between arguments in the extension and (2) an extension defends its arguments from any external attack.
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References
Amgoud, L., Cayrol C.: A reasoning model based on the production of acceptable arguments. Annals of Mathematics and Artificial Intelligence 34, 197–216 (2002)
Amgoud, L., Cayrol C.: Inferring from inconsistency in preference-based argumentation frameworks. International Journal of Approximate Reasoning 29(2), 125–169 (2002)
Amgoud, L., Cayrol, C., LeBerre, D.: Comparing arguments using preference orderings for argument-based reasoning. In: Manaris, B., Marquis, P. (eds.), 8th International Conference on Tools with Artificial Intelligence, pp. 400-403. IEEE, (1996)
Amgoud, L., Dimopoulos, Y., Moraitis, P.: A unified and general framework for argumentation-based negotiation. In: Durfee, E.H., Yokoo, M., Huhns, M.N., Sheory, O. (eds.), 6th International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 158. IFAAMAS, (2007)
Amgoud, L., Kaci, S.: An argumentation framework for merging conflicting knowledge bases. International Journal of Approximate Reasoning 45(2), 321–340 (2007)
Amgoud, L., Prade, H.: Using arguments for making and explaining decisions. Artificial Intelligence 173(3-4), 413–436 (2009)
Amgoud, L., Vesic, S.: Repairing preference-based argumentation frameworks. In: Boutilier, G. (eds.), 21st International Joint Conference on Artificial Intelligence, pp. 665-670. (2009)
Bench-Capon, T.J.M..: Persuasion in practical argument using value-based argumentation frameworks. Journal of Logic and Computation 13(3), 429–448 (2003)
Benferhat, S., Dubois, D., Prade, H.: Argumentative inference in uncertain and inconsistent knowledge bases. In: Heckerman, D., Mamdani, E.H. (eds.), 9th Annual Conference on Uncertainty in Artificial Intelligence, pp. 411-419. Morgan Kaufmann, (1993)
Benferhat, S., Dubois, D., Prade, H.: Some syntactic approaches to the handling of inconsistent knowledge bases: A comparative study Part 2: The prioritized case. Logic at work 24, 473–511 (1998)
Dimopoulos, Y., Moraitis, P., Amgoud, L.: Extending argumentation to make good decisions. In: Rossi, F., Tsouki`as, A. (eds.), 1st International Conference on Algorithmic Decision Theory, pp. 225-236. Springer, (2009)
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)
Dunne, P.E., Hunter, A., McBurney, P., Parsons, S., Wooldridge, M.: Inconsistency tolerance in weighted argument systems. In: Sierra, C., Castelfranchi, C., Decker, K.S., Sichman, J.S. (eds.), 8th International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 851-858. IFAAMAS, (2009)
Kaci, S.: Refined preference-based argumentation frameworks. In: Baroni, P., Giacomin, M., Simari, G. (eds.), 3rd International Conference on Computational Models of Argument, pp. 299-310. IOP Press, (2010)
Kaci, S., Labreuche, C.: Argumentation framework with fuzzy preference relations. In: H¨ullermeier, E., Kruse, R., Hoffmann, F. (eds.), 13th Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems Conference, pp. 554-563. Springer, (2010)
Kaci, S., Labreuche, C.: Preference-based argumentation framework with varied-preference intensity. In: Coelho, H., Studer, R., Wooldridge, M. (eds.), 19th European Conference on Artificial Intelligence, pp. 1003-1004. IOP Press, (2010)
Kaci, S., van der Torre, L.: Preference-based argumentation: Arguments supporting multiple values. International Journal of Approximate Reasoning 48, 730–751 (2008)
Kaci, S., Van der Torre, L., Weydert, E.: On the acceptability of incompatible arguments. In: Mellouli, K. (eds.), 9th European Conferences on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, pp. 247-258. Springer, (2007)
Kaci, S., Van der Torre, L., Weydert, E.: Acyclic argumentation: Attack = conflict+ preference. In: Brewka, G., Coradeschi, S., Perini, A., Traverso, P. (eds.), 17th European Conference on Artificial Intelligence, pp. 725-726. IOS Press, (2006)
Mart´ınez, D.C., Garc´ıa, A.J., Simari, G.R.: An abstract argumentation framework with variedstrength attacks. In: Brewka, G., Lang, J. (eds.), 11th International Conference on Principles of Knowledge Representation and Reasoning, pp. 135-144. AAAI Press, (2008)
Modgil, S.: Reasoning about preferences in argumentation frameworks. Artificial Intelligence 173(9-10), 901–934 (2009)
Perelman, C.: Justice, Law and Argument. Reidel, Dordrecht (1980)
Prakken, H.: Coherence and flexibility in dialogue games for argumentation. Journal of Logic and Computation 15(6), 1009–1040 (2005)
Simari, G.R., Loui, R.P.: A mathematical treatment of defeasible reasoning and its implementation. Artificial Intelligence 53, 125–157 (1992)
Prakken, H., Sartor, G.: Argument-based extended logic programming with defeasible priorities. Journal of Applied Non-Classical Logics 7, 25–75 (1997)
Stolzenburg, F., Garc´ıa, A.J., Ches˜nevar, C.I., Simari, G.R.: Computing generalized specificity. Journal of Applied Non-Classical Logics 13(1), 87–113 (2003)
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Kaci, S. (2011). Preferences in Argumentation Theory. In: Working with Preferences: Less Is More. Cognitive Technologies. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17280-9_6
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DOI: https://doi.org/10.1007/978-3-642-17280-9_6
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