Artificial Intelligence
Graph theoretical structures in logic programs and default theories
Theoretical Computer Science
An abstract, argumentation-theoretic approach to default reasoning
Artificial Intelligence
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Coherence in finite argument systems
Artificial Intelligence
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
Argumentation in artificial intelligence
Artificial Intelligence
Computational properties of argument systems satisfying graph-theoretic constraints
Artificial Intelligence
Elements of Argumentation
A fixed-parameter algorithm for the directed feedback vertex set problem
Journal of the ACM (JACM)
Backdoor Sets of Quantified Boolean Formulas
Journal of Automated Reasoning
Argumentation in Artificial Intelligence
Argumentation in Artificial Intelligence
Backdoors to typical case complexity
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Reasoning in Argumentation Frameworks of Bounded Clique-Width
Proceedings of the 2010 conference on Computational Models of Argument: Proceedings of COMMA 2010
Symmetric argumentation frameworks
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Backdoors to tractable answer-set programming
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Finding odd cycle transversals
Operations Research Letters
Parameterized Complexity
Backdoors to tractable answer-set programming
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
The Multivariate Algorithmic Revolution and Beyond
Algorithms for decision problems in argument systems under preferred semantics
Artificial Intelligence
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We present a new and compelling approach to the efficient solution of important computational problems that arise in the context of abstract argumentation. Our approach makes known algorithms defined for restricted fragments generally applicable, at a computational cost that scales with the distance from the fragment. Thus, in a certain sense, we gradually augment tractable fragments. Surprisingly, it turns out that some tractable fragments admit such an augmentation and that others do not. More specifically, we show that the problems of credulous and skeptical acceptance are fixed-parameter tractable when parameterized by the distance from the fragment of acyclic argumentation frameworks. Other tractable fragments such as the fragments of symmetrical and bipartite frameworks seem to prohibit an augmentation: the acceptance problems are already intractable for frameworks at distance 1 from the fragments. For our study we use a broad setting and consider several different semantics. For the algorithmic results we utilize recent advances in fixed-parameter tractability.