Artificial Intelligence
An abstract, argumentation-theoretic approach to default reasoning
Artificial Intelligence
Acceptability of arguments as `logical uncertainty'
ECSQARU '93 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Automated Reasoning with Merged Contradictory Information Whose Reliability Depends on Topics
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Defeasible logic programming: an argumentative approach
Theory and Practice of Logic Programming
System Z: a natural ordering of defaults with tractable applications to nonmonotonic reasoning
TARK '90 Proceedings of the 3rd conference on Theoretical aspects of reasoning about knowledge
Argumentation Semantics for Defeasible Logic
Journal of Logic and Computation
Bridging the Gap between Abstract Argumentation Systems and Logic
SUM '09 Proceedings of the 3rd International Conference on Scalable Uncertainty Management
An axiomatic account of formal argumentation
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
On the relation between argumentation and non-monotonic coherence based entailment
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
How to infer from inconsistent beliefs without revising
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Instantiating abstract argumentation with classical logic arguments: Postulates and properties
Artificial Intelligence
On the issue of reinstatement in argumentation
JELIA'06 Proceedings of the 10th European conference on Logics in Artificial Intelligence
Symmetric argumentation frameworks
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Stable semantics in logic-based argumentation
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
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Logic-based argumentation systems are developed for reasoning with inconsistent information. They consist of a set of arguments, attacks among them and a semantics for the evaluation of arguments. Preferred semantics is favored in the literature since it ensures the existence of extensions (i.e., acceptable sets of arguments), and it guarantees a kind of maximality, accepting thus arguments whenever possible. This paper proposes the first study on the outcomes under preferred semantics of logic-based argumentation systems that satisfy basic rationality postulates. It focuses on systems that are grounded on Tarskian logics, and delimits the number of preferred extensions they may have. It also characterizes both their extensions and their sets of conclusions that are drawn from knowledge bases. The results are disappointing since they show that in the best case, the preferred extensions of a system are computed from the maximal consistent subbases of the knowledge base under study. In this case, the system is coherent, that is preferred extensions are stable ones. Moreover, we show that both semantics are useless in thic case since they ensure exactly the same result as naive semantics. Apart from this case, the outcomes of argumentation systems are counter-intuitive.