Abstract
Given an argumentation framework AF = (Ar, R) - with Ar a finite set of arguments and R ⊆ Ar ×Ar - the attack relation identifying the graph G - we study how the grounded labelling of a generic argument a εAr varies in all the subgraphs of G Since this is an intractable problem of above-polynomial complexity, we present two non-naïve algorithms to find the set of all the subgraphs where the grounded semantic assigns to argument a specific label l ε{in, out, undec}. We report the results of a series of empirical tests over graphs of increasing complexity. The value of researching the above problem is two-fold. First, knowing how an argument behaves in all the subgraphs represents strategic information for arguing agents. Second, the algorithms can be applied to the computation of the recently introduced probabilistic argumentation frameworks.
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References
Dung, P.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77, 321–357 (1995)
Dung, P., Thang, P.: Towards (Probabilistic) Argumentation for Jury-based Dispute Resolution. In: COMMA 2010, pp. 171–182. IOS Press, Amsterdam (2010)
Li, H., Oren, N., Norman, T.J.: Probabilistic Argumentation Frameworks. In: 1st TAFA, JICAI 2011, Barcellona, Spain (2011)
Baroni, P., Caminada, M., Giacomin, M.: An introduction to argumentation semantics. Knowledge Eng. Review 26(4), 365–410 (2011)
Dunne, P.E., Wooldridge, M.: Complexity of abstract argumentation. In: Argumentation in Artificial Intelligence, pp. 85–104. Springer US (2009)
Hunter, A.: A probabilistic approach to modeling uncertain logical arguments. International Journal of Approximate Reasoning 54(1), 47–81 (2013)
Thimm, M.: Probabilistic Semantics for Abstract Argumentation. In: Proceedings. of 20th European Conference of Artificial Intelligence, pp. 750–755. IOS Press (2012)
Boella, G., Kaci, S., van der Torre, L.: Dynamics in argumentation with single extensions: Abstraction principles and the grounded extension. In: Sossai, C., Chemello, G. (eds.) ECSQARU 2009. LNCS, vol. 5590, pp. 107–118. Springer, Heidelberg (2009)
Baumann, R.: Splitting an argumentation framework. In: Delgrande, J.P., Faber, W. (eds.) LPNMR 2011. LNCS, vol. 6645, pp. 40–53. Springer, Heidelberg (2011)
Charwat, G.: Tree-Decomposition based Algorithms for Abstract Argumentation Frameworks. Thesis, Vienna University of Technology (February 2012)
Dondio, P.: Probabilistic Argumentation Frameworks: Basic Properties and Computation, Highlights on Practical Applications of Multi-Agent Systems, pp. 263–279. Springer (2013)
Cayrol, C., Dupin, F., Lagasquie-Schiex, M.: Change in abstract argumentation frameworks: adding an argument. Journal of Artificial Intellgence Research 38(1), 49–84 (2010)
Nofal, S., Dunne, P.E., Atkinson, K.: Towards Experimental Algorithms for Abstract Argumentation. In: COMMA, pp. 217–228 (2012)
Modgil, S., Caminada, M.: Proof theories and algorithms for abstract argumentation frameworks. In: Argumentation in Artificial Intelligence, pp. 105–129. Springer US (2009)
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Dondio, P. (2013). Computing the Grounded Semantics in all the Subgraphs of an Argumentation Framework: An Empirical Evaluation. In: Leite, J., Son, T.C., Torroni, P., van der Torre, L., Woltran, S. (eds) Computational Logic in Multi-Agent Systems. CLIMA 2013. Lecture Notes in Computer Science(), vol 8143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40624-9_8
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DOI: https://doi.org/10.1007/978-3-642-40624-9_8
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