A theory of diagnosis from first principles
Artificial Intelligence
Linear resolution for consequence finding
Artificial Intelligence
A graph-theoretic approach to default logic
Information and Computation
An abstract, argumentation-theoretic approach to default reasoning
Artificial Intelligence
On kernels, defaults and even graphs
Annals of Mathematics and Artificial Intelligence
Credulous and Sceptical Argument Games for Preferred Semantics
JELIA '00 Proceedings of the European Workshop on Logics in Artificial Intelligence
Computing Extensions of Default Theories
ECSQAU Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Synthesis of Proof Procedures for Default Reasoning
LOPSTR '96 Proceedings of the 6th International Workshop on Logic Programming Synthesis and Transformation
Preferred arguments are harder to compute than stable extensions
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Towards efficient default reasoning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Dialectical Proof Theories for the Credulous Preferred Semantics of Argumentation Frameworks
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Optimal utterances in dialogue protocols
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Argumentation in artificial intelligence
Artificial Intelligence
An application of formal argumentation: Fusing Bayesian networks in multi-agent systems
Artificial Intelligence
An Application of Formal Argumentation: Fusing Bayes Nets in MAS
Proceedings of the 2006 conference on Computational Models of Argument: Proceedings of COMMA 2006
Computing Preferred Extensions for Argumentation Systems with Sets of Attacking Arguments
Proceedings of the 2006 conference on Computational Models of Argument: Proceedings of COMMA 2006
Reasoning in Argumentation Frameworks Using Quantified Boolean Formulas
Proceedings of the 2006 conference on Computational Models of Argument: Proceedings of COMMA 2006
A labeling approach to the computation of credulous acceptance in argumentation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Enhancing dung's preferred semantics
FoIKS'10 Proceedings of the 6th international conference on Foundations of Information and Knowledge Systems
Towards fixed-parameter tractable algorithms for abstract argumentation
Artificial Intelligence
Complexity-sensitive decision procedures for abstract argumentation
Artificial Intelligence
Algorithms for decision problems in argument systems under preferred semantics
Artificial Intelligence
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The preferred semantics for argumentation frameworks seems to capture well the intuition behind the stable semantics while avoiding several of its drawbacks. Although the stable semantics has been thoroughly studied, and several algorithms have been proposed for solving problems related to it, it seems that the algorithmic side of the preferred semantics has received less attention. In this paper, we propose algorithms, based on the enumeration of some subsets of a given set of arguments, for the following tasks: 1) deciding if a given argument is in a preferred extension of a given argumentation framework; 2) deciding if the argument is in all the preferred extensions of the framework; 3) generating the preferred extensions of the framework.