Abstract
Domains, such as Ambient Intelligence and Social Networks, are characterized by some common features including distribution of the available knowledge, entities with different backgrounds, viewpoints and operational environments, and imperfect knowledge. Multi-Context Systems (MCS) has been proposed as a natural representation model for such environments, while recent studies have proposed adding non-monotonic features to MCS to address the issues of incomplete, uncertain and ambiguous information. In previous works, we introduced a non-monotonic extension to MCS and an argument-based reasoning model that handle imperfect context information based on defeasible argumentation. Here we propose alternative variants that integrate features such as partial preferences, ambiguity propagating and team defeat, and study the relations between the different variants in terms of conclusions being drawn in each case.
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This work was carried out during the tenure of an ERCIM ”Alain Bensoussan” Fellowship Programme.
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References
Giunchiglia, F., Serafini, L.: Multilanguage Hierarchical Logics or: How we can do Without Modal Logics. Artificial Intelligence 65(1), 29–70 (1994)
Ghidini, C., Giunchiglia, F.: Local Models Semantics, or contextual reasoning = locality + compatibility. Artificial Intelligence 127(2), 221–259 (2001)
Roelofsen, F., Serafini, L.: Minimal and Absent Information in Contexts. In: IJCAI, pp. 558–563 (2005)
Brewka, G., Roelofsen, F., Serafini, L.: Contextual Default Reasoning. In: IJCAI, pp. 268–273 (2007)
Bikakis, A., Antoniou, G.: Contextual Argumentation in Ambient Intelligence. In: Erdem, E., Lin, F., Schaub, T. (eds.) LPNMR 2009. LNCS, vol. 5753, pp. 30–43. Springer, Heidelberg (2009)
Bikakis, A., Antoniou, G.: Defeasible Contextual Reasoning with Arguments in Ambient Intelligence. IEEE TKDE 22(11), 1492–1506 (2010)
Antoniou, G., Bikakis, A., Papatheodorou, C.: Reasoning with Imperfect Context and Preference Information in Multi-Context Systems. In: Catania, B., Ivanović, M., Thalheim, B. (eds.) ADBIS 2010. LNCS, vol. 6295, pp. 1–12. Springer, Heidelberg (2010)
Antoniou, G., Billington, D., Governatori, G., Maher, M.J., Rock, A.: A Family of Defeasible Reasoning Logics and its Implementation. In: ECAI, pp. 459–463 (2000)
Governatori, G., Maher, M.J., Antoniou, G., Billington, D.: Argumentation Semantics for Defeasible Logic. Journal of Logic and Computation 14(5), 675–702 (2004)
Brewka, G., Eiter, T.: Argumentation Context Systems: A Framework for Abstract Group Argumentation. In: Erdem, E., Lin, F., Schaub, T. (eds.) LPNMR 2009. LNCS, vol. 5753, pp. 44–57. Springer, Heidelberg (2009)
Thimm, M., Kern-Isberner, G.: A Distributed Argumentation Framework using Defeasible Logic Programming. In: COMMA, pp. 381–392. IOS Press, Amsterdam (2008)
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Bikakis, A., Antoniou, G. (2011). Partial Preferences and Ambiguity Resolution in Contextual Defeasible Logic. In: Delgrande, J.P., Faber, W. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2011. Lecture Notes in Computer Science(), vol 6645. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20895-9_18
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DOI: https://doi.org/10.1007/978-3-642-20895-9_18
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