Abstract
The area of inconsistent ontological knowledge base query answering studies the problem of inferring from an inconsistent ontology. To deal with such a situation, different semantics have been defined in the literature (e.g. AR, IAR, ICR). Argumentation theory can also be used to draw conclusions under inconsistency. Given a set of arguments and attacks between them, one applies a particular semantics (e.g. stable, preferred, grounded) to calculate the sets of accepted arguments and conclusions. However, it is not clear what are the similarities and differences of semantics from ontological knowledge base query answering and semantics from argumentation theory. This paper provides the answer to that question. Namely, we prove that: (1) sceptical acceptance under stable and preferred semantics corresponds to ICR semantics; (2) universal acceptance under stable and preferred semantics corresponds to AR semantics; (3) acceptance under grounded semantics corresponds to IAR semantics. We also prove that the argumentation framework we define satisfies the rationality postulates (e.g. consistency, closure).
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References
Amgoud, L., Besnard, P.: Bridging the gap between abstract argumentation systems and logic. In: Godo, L., Pugliese, A. (eds.) SUM 2009. LNCS, vol. 5785, pp. 12–27. Springer, Heidelberg (2009)
Amgoud, L., Cayrol, C.: Inferring from inconsistency in preference-based argumentation frameworks. Journal of Automated Reasoning 29 (2), 125–169 (2002)
Baget, J.-F., Mugnier, M.-L.: The Complexity of Rules and Constraints. JAIR 16, 425–465 (2002)
Baget, J.-F., Mugnier, M.-L., Rudolph, S., Thomazo, M.: Walking the complexity lines for generalized guarded existential rules. In: Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI 2011), pp. 712–717 (2011)
Benferhat, S., Dubois, D., Prade, H.: Argumentative inference in uncertain and inconsistent knowledge bases. In: Proceedings of the 9th Conference on Uncertainty in Artificial intelligence (UAI 1993), pp. 411–419 (1993)
Besnard, P., Hunter, A.: Elements of Argumentation. MIT Press (2008)
Bex, F.J., Modgil, S.J., Prakken, H., Reed, C.: On logical specifications of the argument interchange format. Journal of Logic and Computation (2013)
Bienvenu, M.: On the complexity of consistent query answering in the presence of simple ontologies. In: Proc. of AAAI (2012)
Black, E., Hunter, A., Pan, J.Z.: An argument-based approach to using multiple ontologies. In: Godo, L., Pugliese, A. (eds.) SUM 2009. LNCS, vol. 5785, pp. 68–79. Springer, Heidelberg (2009)
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 (IJCAI 1995), pp. 1443–1448 (1995)
Chein, M., Mugnier, M.-L.: Graph-based Knowledge Representation and Reasoning—Computational Foundations of Conceptual Graphs. Advanced Information and Knowledge Processing. Springer (2009)
Chesnevar, C., McGinnis, J., Modgil, S., Rahwan, I., Reed, C., Simari, G., South, M., Vreeswijk, G., Willmott, S.: Towards an argument interchange format. Knowledge Engineering Review 21(4), 293–316 (2006)
Dix, J., Parsons, S., Prakken, H., Simari, G.R.: Research challenges for argumentation. Computer Science - R&D 23(1), 27–34 (2009)
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)
Lembo, D., Lenzerini, M., Rosati, R., Ruzzi, M., Savo, D.F.: Inconsistency-tolerant semantics for description logics. In: Proc. of RR, pp. 103–117 (2010)
Lenzerini, M.: Data integration: A theoretical perspective. In: Proc. of PODS 2002 (2002)
Modgil, S.J., Prakken, H.: A general account of argumentation with preferences. Artificial Intelligence Journal (2013)
Rahwan, I., Zablith, F., Reed, C.: Laying the foundations for a world wide argument web. Artificial Intelligence 171(10-15), 897–921 (2007)
Vesic, S.: Maxi-consistent operators in argumentation. In: 20th European Conference on Artificial Intelligence (ECAI 2012), pp. 810–815 (2012)
Vesic, S., van der Torre, L.: Beyond maxi-consistent argumentation operators. In: del Cerro, L.F., Herzig, A., Mengin, J. (eds.) JELIA 2012. LNCS, vol. 7519, pp. 424–436. Springer, Heidelberg (2012)
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Croitoru, M., Vesic, S. (2013). What Can Argumentation Do for Inconsistent Ontology Query Answering?. In: Liu, W., Subrahmanian, V.S., Wijsen, J. (eds) Scalable Uncertainty Management. SUM 2013. Lecture Notes in Computer Science(), vol 8078. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40381-1_2
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DOI: https://doi.org/10.1007/978-3-642-40381-1_2
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