Abstract
Dung’s abstract argumentation model consists of a set of arguments and a binary relation encoding attacks among arguments. Different acceptability semantics have been defined for evaluating the arguments. What is worth noticing is that the model completely abstracts from the applications to which it can be applied. Thus, it is not clear what are the results that can be returned in a given application by each semantics. This paper answers this question. For that purpose, we start by plunging the model in a real application. That is, we assume that we have an inconsistent knowledge base (KB) containing formulas of an abstract monotonic logic. From this base, we show how to define arguments. Then, we characterize the different semantics in terms of the subsets of the KB that are returned by each extension. We show a full correspondence between maximal consistent subbases of a KB and maximal conflict-free sets of arguments. We show also that stable and preferred extensions choose randomly some consistent subbases of a base. Finally, we investigate the results of three argumentation systems that use well-known attack relations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Amgoud, L., Besnard, P.: Bridging the gap between abstract argumentation systems and logic. In: Proceedings of the 3rd International Conference on Scalable Uncertainty, pp. 12–27 (2009)
Amgoud, L., Cayrol, C.: Inferring from inconsistency in preference-based argumentation frameworks. International Journal of Automated Reasoning 29(2), 125–169 (2002)
Amgoud, L., Parsons, S., Maudet, N.: Arguments, dialogue, and negotiation. In: Proceedings of the 14th European Conference on Artificial Intelligence (ECAI 2000), pp. 338–342. IOS Press, Amsterdam (2000)
Amgoud, L., Prade, H.: Using arguments for making and explaining decisions. Artificial Intelligence Journal 173, 413–436 (2009)
Baroni, P., Giacomin, M., Guida, G.: Scc-recursiveness: a general schema for argumentation semantics. Artificial Intelligence Journal 168, 162–210 (2005)
Besnard, P., Hunter, A.: Elements of Argumentation. MIT Press, Cambridge (2008)
Bonet, B., Geffner, H.: Arguing for decisions: A qualitative model of decision making. In: Proceedings of International Conference on Uncertainty in Artificial Intelligence (UAI 1996), pp. 98–105 (1996)
Caminada, M.: Semi-stable semantics. In: Proceedings of the 1st International Conference on Computational Models of Argument, pp. 121–130 (2006)
Caminada, M., Amgoud, L.: On the evaluation of argumentation formalisms. Artificial Intelligence Journal 171(5-6), 286–310 (2007)
Cayrol, C.: On the relation between argumentation and non-monotonic coherence-based entailment. In: Proceedings of the 14th International Joint Conference on Artificial Intelligence, pp. 1443–1448 (1995)
Dung, P., Mancarella, P., Toni, F.: Computing ideal skeptical argumentation. Artificial Intelligence Journal 171, 642–674 (2007)
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)
Kakas, A., Moraitis, P.: Argumentation based decision making for autonomous agents. In: Proceedings of the 2nd International Joint Conference on Autonomous Agents and Multi-Agents systems (AAMAS 2003), pp. 883–890 (2003)
Kraus, S., Sycara, K., Evenchik, A.: Reaching agreements through argumentation: a logical model and implementation. Journal of Artificial Intelligence 104, 1–69 (1998)
Prakken, H.: Coherence and flexibility in dialogue games for argumentation. Journal of Logic and Computation 15, 1009–1040 (2005)
Simari, G., Loui, R.: A mathematical treatment of defeasible reasoning and its implementation. AIJ 53, 125–157 (1992)
Tarski, A.: On Some Fundamental Concepts of Metamathematics. Logic, Semantics, Metamathematic. Edited and translated by J. H. Woodger. Oxford Uni. Press, Oxford (1956)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Amgoud, L., Besnard, P. (2010). A Formal Analysis of Logic-Based Argumentation Systems. In: Deshpande, A., Hunter, A. (eds) Scalable Uncertainty Management. SUM 2010. Lecture Notes in Computer Science(), vol 6379. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15951-0_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-15951-0_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15950-3
Online ISBN: 978-3-642-15951-0
eBook Packages: Computer ScienceComputer Science (R0)