Abstract
We propose a framework to allow an agent to cope with inconsistent beliefs and to handle conflicting inferences. Our approach is based on a well-established line of research on assumption-based argumentation frameworks and defeasible reasoning. We propose a language to allow defeasible assumptions and context-sensitive priorities to be explicitly expressed and reasoned about by the agent. Our work reveals some interesting problems to conditional priority-based argumentation and establishes the fundamental properties of these frameworks. We also establish a sufficient condition for a conditional priority-based argumentation to have a unique stable extension based on the notion of stratification.
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References
Amgoud, L., Cayrol, C.: Inferring from inconsistency in preference-based argumentation frameworks. J. Autom. Reason. 29(2), 125–169 (2002)
Antoniou, G.: Defeasible logic with dynamic priorities. Int. J. Intell. Syst. 19(5), 463–472 (2004)
Apt, K.R., Blair, H.A.: Arithmetic classification of perfect models of stratified programs. Fundam. Inform. 14(3), 339–343 (1991)
Apt, K.R., Blair, H.A., Walker, A.: Towards a theory of declarative knowledge. In: Minker, J. (ed.) Foundations of deductive databases and logic programming, pp. 89–148. Morgan Kaufmann Publishers Inc., San Francisco (1988)
Bench-Capon, T.J.M.: Persuasion in Practical Argument Using Value-based Argumentation Frameworks. J Logic Computation 13(3), 429–448 (2003)
Bondarenko, A., Dung, P.M., Kowalski, R.A., Toni, F.: An abstract, argumentation-theoretic approach to default reasoning. Artificial Intelligence Journal 93, 63–101 (1997)
Brewka, G.: Reasoning about priorities in default logic. In: AAAI, pp. 940–945 (1994)
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)
Dung, P.M., Mancarella, P., Toni, F.: Computing ideal sceptical argumentation. Artif. Intell. 171(10-15), 642–674 (2007)
Dung, P.M., Son, T.C.: An argument-based approach to reasoning with specificity. Artif. Intell. 133(1-2), 35–85 (2001)
Elvang-Gøransson, M., Hunter, A.: Argumentative logics: Reasoning with classically inconsistent information. Data Knowl. Eng. 16(2), 125–145 (1995)
Elvang-Gøransson, M., Krause, P., Fox, J.: Acceptability of arguments as ‘logical uncertainty’. In: ECSQARU, pp. 85–90 (1993)
Gelfond, M.: On stratified autoepistemic theories. In: AAAI, pp. 207–211 (1987)
Governatori, G., Maher, M.J., Antoniou, G., Billington, D.: Argumentation semantics for defeasible logic. J. Log. Comput. 14(5), 675–702 (2004)
Horty, J.F., Thomason, R.H., Touretzky, D.S.: A skeptical theory of inheritance in nonmonotonic semantic networks. Artif. Intell. 42(2-3), 311–348 (1990)
Prakken, H., Sartor, G.: Argument-based extended logic programming with defeasible priorities. Journal of Applied Non–classical Logics 7, 25–75 (1997)
Vo, Q.B., Foo, N.Y.: Reasoning about action: An argumentation-theoretic approach. Journal of Artificial Intelligence Research 24, 465–518 (2005)
Vo, Q.B., Foo, N.Y., Thurbon, J.: Semantics for a theory of defeasible reasoning. Annals of Mathematics and Artificial Intelligence 44(1-2), 87–119 (2005)
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Vo, Q.B. (2008). An Argumentation Framework Based on Conditional Priorities. In: Ho, TB., Zhou, ZH. (eds) PRICAI 2008: Trends in Artificial Intelligence. PRICAI 2008. Lecture Notes in Computer Science(), vol 5351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89197-0_46
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DOI: https://doi.org/10.1007/978-3-540-89197-0_46
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