Abstract argumentation systems
Artificial Intelligence
ACM Computing Surveys (CSUR)
Defeasible logic programming: an argumentative approach
Theory and Practice of Logic Programming
On the evaluation of argumentation formalisms
Artificial Intelligence
Elements of Argumentation
A Level-based Approach to Computing Warranted Arguments in Possibilistic Defeasible Programming
Proceedings of the 2008 conference on Computational Models of Argument: Proceedings of COMMA 2008
Argumentation in Artificial Intelligence
Argumentation in Artificial Intelligence
On the acceptability of arguments in preference-based argumentation
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Computing dialectical trees efficiently in possibilistic defeasible logic programming
LPNMR'05 Proceedings of the 8th international conference on Logic Programming and Nonmonotonic Reasoning
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
Maximal ideal recursive semantics for defeasible argumentation
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
Extending a temporal defeasible argumentation framework with possibilistic weights
JELIA'12 Proceedings of the 13th European conference on Logics in Artificial Intelligence
Hi-index | 0.00 |
In this paper we define a recursive semantics for warrant in a general defeasible argumentation framework by formalizing a notion of collective (non-binary) conflict among arguments. This allows us to ensure direct and indirect consistency (in the sense of Caminada and Amgoud) without distinguishing between direct and indirect conflicts. Then, the general defeasible argumentation framework is extended by allowing to attach levels of preference to defeasible knowledge items and by providing a level-wise definition of warranted and blocked conclusions. Finally, we formalize the warrant recursive semantics for the particular framework of Possibilistic Defeasible Logic Programming, characterize the unique output program property and design an efficient algorithm for computing warranted conclusions in polynomial space.