ACM Computing Surveys (CSUR)
A logic-based theory of deductive arguments
Artificial Intelligence
Defeasible reasoning with variable degrees of justification
Artificial Intelligence
Defeasible logic programming: an argumentative approach
Theory and Practice of Logic Programming
Argument-based critics and recommenders: a qualitative perspective on user support systems
Data & Knowledge Engineering - Special issue: WIDM 2004
On the evaluation of argumentation formalisms
Artificial Intelligence
Knowledge and information distribution leveraged by intelligent agents
Knowledge and Information Systems
An axiomatic account of formal argumentation
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Journal of Artificial Intelligence Research
A characterization of collective conflict for defeasible argumentation
Proceedings of the 2010 conference on Computational Models of Argument: Proceedings of COMMA 2010
A computational method for defeasible argumentation based on a recursive warrant semantics
IBERAMIA'10 Proceedings of the 12th Ibero-American conference on Advances in artificial intelligence
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Possibilistic Defeasible Logic Programming (P-DeLP) is an argumentation framework based on logic programming which incorporates a treatment of possibilistic uncertainty at object-language level. In P-DeLP, the closure of justified conclusions is not always consistent, which has been detected to be an anomaly in the context of so-called rationality postulates for rule-based argumentation systems. In this paper we present a novel level-based approach to computing warranted arguments in P-DeLP which ensures the above rationality postulate. We also show that our solution presents some advantages in comparison with the use of a transposition operator applied on strict rules.