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Dynamics of knowledge in DeLP through Argument Theory Change

Published online by Cambridge University Press:  25 January 2012

MARTÍN O. MOGUILLANSKY
Affiliation:
National Research Council (CONICET), AI R&D Lab (LIDIA), Department of Computer Science and Engineering (DCIC), Universidad Nacional del Sur (UNS), Argentina (e-mail: [email protected], [email protected], [email protected], [email protected], [email protected])
NICOLÁS D. ROTSTEIN
Affiliation:
National Research Council (CONICET), AI R&D Lab (LIDIA), Department of Computer Science and Engineering (DCIC), Universidad Nacional del Sur (UNS), Argentina (e-mail: [email protected], [email protected], [email protected], [email protected], [email protected])
MARCELO A. FALAPPA
Affiliation:
National Research Council (CONICET), AI R&D Lab (LIDIA), Department of Computer Science and Engineering (DCIC), Universidad Nacional del Sur (UNS), Argentina (e-mail: [email protected], [email protected], [email protected], [email protected], [email protected])
ALEJANDRO J. GARCÍA
Affiliation:
National Research Council (CONICET), AI R&D Lab (LIDIA), Department of Computer Science and Engineering (DCIC), Universidad Nacional del Sur (UNS), Argentina (e-mail: [email protected], [email protected], [email protected], [email protected], [email protected])
GUILLERMO R. SIMARI
Affiliation:
National Research Council (CONICET), AI R&D Lab (LIDIA), Department of Computer Science and Engineering (DCIC), Universidad Nacional del Sur (UNS), Argentina (e-mail: [email protected], [email protected], [email protected], [email protected], [email protected])

Abstract

This article is devoted to the study of methods to change defeasible logic programs (de.l.p.s) which are the knowledge bases used by the Defeasible Logic Programming (DeLP) interpreter. DeLP is an argumentation formalism that allows to reason over potentially inconsistent de.l.p.s. Argument Theory Change (ATC) studies certain aspects of belief revision in order to make them suitable for abstract argumentation systems. In this article, abstract arguments are rendered concrete by using the particular rule-based defeasible logic adopted by DeLP. The objective of our proposal is to define prioritized argument revision operators à la ATC for de.l.p.s, in such a way that the newly inserted argument ends up undefeated after the revision, thus warranting its conclusion. In order to ensure this warrant, the de.l.p. has to be changed in concordance with a minimal change principle. To this end, we discuss different minimal change criteria that could be adopted. Finally, an algorithm is presented, implementing the argument revision operations.

Type
Regular Papers
Copyright
Copyright © Cambridge University Press 2012 

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References

Alchourrón, C., Gärdenfors, P. and Makinson, D. 1985. On the logic of theory change: Partial meet contraction and revision functions. The Journal of Symbolic Logic 50, 510530.Google Scholar
Baroni, P., Cerutti, F., Giacomin, M. and Simari, G. R., Eds. 2010. Computational models of argument In Proceedings. of COMMA 2010. Frontiers in Artificial Intelligence and Applications, Vol. 216. IOS Press, Italy, September 8–10.Google Scholar
Baroni, P. and Giacomin, M. 2007. On principle-based evaluation of extension-based argumentation semantics. Artificial Intelligence 171 (10–15), 675700.CrossRefGoogle Scholar
Benferhat, S., Dubois, D. and Prade, H. 1995. How to infer from inconsistent beliefs without revising. In Proceedings. of IJCAI'95, Montreal, Canada, 14491455.Google Scholar
Billington, D., Antoniou, G., Governatori, G. and Maher, M. 1999. Revising nonmonotonic theories: The case of defeasible logic. KI-99: Advances in Artificial Intelligence, 695–695.Google Scholar
Black, E. and Hunter, A. 2009. An inquiry dialogue system. Autonomous Agents and Multi-Agent Systems 19 (2), 173209.CrossRefGoogle Scholar
Boella, G., Costa Perera, C. D., Tettamanzi, A. and van der Torre, L. 2008a. Dung Argumentation and AGM Belief Revision. In 5th International Workshop on Argumentation in Multi-Agent Systems, ArgMAS 2008, Estoril, Portugal, May 12, 2008.Google Scholar
Boella, G., CostaPerera, C. D. Perera, C. D., Tettamanzi, A. and van der Torre, L. 2008b. Making others believe what they want. Artificial Intelligence in Theory and Practice II, 215–224.Google Scholar
Cayrol, C., de Saint Cyr, F. D. and Lagasquie Schiex, M. C. 2008. Revision of an Argumentation System. In Proceedings. of The International Conference on Principles of Knowledge Representation and Reasoning, KR 2008, Sydney, Australia, 124134.Google Scholar
Chesñevar, C., Maguitman, A. and Simari, G. 2007. Emerging artificial intelligence applications in computer engineering. In Frontiers in Artificial Intelligence and Applications, vol. 160. IOS Press, Amsterdam, Netherlands, Chapter Recommender Systems based on Argumentation, 5370.Google Scholar
Chesñevar, C. I., Maguitman, A. G. and Loui, R. P. 2000. Logical models of argument. ACM Computing Surveys 32 (4), 337383.Google Scholar
Dalal, M. 1988. Investigations into a theory of knowledge base revision. In AAAI. AAAI Press, 475479.Google Scholar
Delgrande, J., Schaub, T., Tompits, H. and Woltran, S. 2008. Belief revision of logic programs under answer set semantics. In Proceedings. of the 11th International Conference on Principles of Knowledge Representation and Reasoning, Sydney, Australia, 411421.Google Scholar
Dung, P. 1995. On the acceptability of arguments and its fundamental role in nonmonotonic reasoning and logic programming and n-person games. Artificial Intelligence Journal 77, 321357.Google Scholar
Falappa, M., Kern-Isberner, G. and Simari, G. 2002. Explanations, belief revision and defeasible reasoning. Artificial Intelligence Journal 141 (1–2), 128.CrossRefGoogle Scholar
García, A. J., Dix, J. and Simari, G. R. 2009. Argument-based logic programming. In Argumentation in Artificial Intelligence, Rahwan, I. and Simari, G. R., Eds. Springer, New York, Chapter 8, 153172.Google Scholar
García, A. J., Rotstein, N. D. and Simari, G. R. 2007. Dialectical explanations in defeasible argumentation. In ECSQARU, 295–307.Google Scholar
García, A. J. and Simari, G. R. 2004. Defeasible logic programming: An argumentative approach. TPLP 4 (1–2), 95138.Google Scholar
Gärdenfors, P. 1981. An epistemic approach to conditionals. American Philosophical Quarterly 18 (3), 203211.Google Scholar
Gómez, S. A., Chesñevar, C. I. and Simari, G. R. 2010. Reasoning with inconsistent ontologies through argumentation. Applied Artificial Intelligence 24 (1), 102148.Google Scholar
Hansson, S. O. 1991. Belief contraction without recovery. Studia Logica 50, 251260.Google Scholar
Hansson, S. O. 1993. Reversing the levi identity. Journal of Philosophical Logic 22 (6), 637669.Google Scholar
Hansson, S. O. 1994. Kernel contraction. Journal of Symbolic Logic 59, 845859.CrossRefGoogle Scholar
Hansson, S. O. 1997. Semi-revision. Journal of Applied Non-Classical Logic 7, 151175.CrossRefGoogle Scholar
Hansson, S. O. 1999. A Textbook of Belief Dynamics: Theory Change and Database Updating. Springer, Kluwer Academic Publishers, Dordrecht.CrossRefGoogle Scholar
Hansson, S. O. and Wassermann, R. 2002. Local change. Studia Logica 70 (1), 4976.Google Scholar
Levi, I. 1977. Subjunctives, dispositions, and chances. Synthèse 34, 423455.CrossRefGoogle Scholar
Moguillansky, M., Rotstein, N., Falappa, M., García, A. and Simari, G. 2008. Argument theory change applied to DeLP. In AAAI 2008. AAAI Press, 132137.Google Scholar
Moguillansky, M., Wassermann, R. and Falappa, M. 2011. Inconsistent-tolerant base revision through argument theory change. Logic Journal of the IGPL (JIGPAL). URL: http://jigpal.oxfordjournals.org/content/early/2011/06/10/jigpal.jzr029.abstract?keytype=ref&ijkey=qhOYI0yUs5zdSz9Google Scholar
Moguillansky, M. O., Rotstein, N. D., Falappa, M. A., García, A. J. and Simari, G. R. 2010. Argument theory change through defeater activation. See Baroni et al. (2010), 359–366.Google Scholar
Paglieri, F. and Castelfranchi, C. 2006. The Toulmin Test: Framing Argumentation within Belief Revision Theories. Springer, Berlin. 359377.Google Scholar
Pollock, J. L. and Gillies, A. S. 2000. Belief revision and epistemology. Synthese 122 (1–2), 6992.CrossRefGoogle Scholar
Prakken, H. and Vreeswijk, G. 2001. Logical systems for defeasible argumentation. In Handbook of Philosophical Logic, Gabbay, D. M. and Guenthner, F., Eds. vol. 4. Kluwer Academic Publishers, Dordrecht/Boston/London, 219318.Google Scholar
Rotstein, N., Moguillansky, M., García, A. and Simari, G. 2010. A dynamic abstract argumentation framework. See Baroni et al. (2010), 427–438.Google Scholar
Rotstein, N., Moguillansky, M. and Simari, G. 2009. Dialectical abstract argumentation: A characterization of the marking criterion. In Proceedings of the Twenty-first International Joint Conference on Artificial Intelligence (IJCAI 2009), 898–903.Google Scholar
Rotstein, N. D., García, A. J. and Simari, G. R. 2007. Reasoning from desires to intentions: A dialectical framework. In AAAI 2007. AAAI Press, 136141.Google Scholar
Rotstein, N. D., Moguillansky, M. O., Falappa, M. A., García, A. J. and Simari, G. R. 2008. Argument theory change: Revision upon warrant. In COMMA (Computational Models of Argument), Besnard, P., Doutre, S. and Hunter, A., Eds. Frontiers in Artificial Intelligence and Applications, vol. 172. IOS Press, 336347.Google Scholar
Thimm, M. and Kern-Isberner, G. 2008. A distributed argumentation framework using defeasible logic programming. In COMMA. IOS Press, 381392.Google Scholar