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We present various new concepts and results related to abstract dialectical frameworks (ADFs), a powerful generalization of Dung's argumentation frameworks (AFs). In particular, we show how the existing definitions of stable and preferred semantics which are restricted to the subcase of so-called bi-polar ADFs can be improved and generalized to arbitrary(More)
Argumentation is nowadays a core topic in AI research. Understanding computational and representational aspects of abstract argumentation frameworks (AFs) is a central topic in the study of argumentation. The study of realizability of AFs aims at understanding the expressive power of AFs under different semantics. We propose and study the AF synthesis(More)
Dung's famous abstract argumentation frameworks represent the core formalism for many problems and applications in the field of argumentation which significantly evolved within the last decade. Recent work in the field has thus focused on implementations for these frameworks, whereby one of the main approaches is to use Answer-Set Programming (ASP). While(More)
Answer Set Programming is a well-established paradigm of declarative programming in close relationship with other declarative formalisms such as SAT Modulo Theories, Constraint Handling Rules, PDDL and many others. Since its first informal editions, ASP systems are compared in the nowadays customary ASP Competition. The fourth ASP Competition, held in(More)
dialectical frameworks (ADFs) have recently been proposed as a versatile generalization of Dung's abstract argumentation frameworks (AFs). In this paper, we present a comprehensive analysis of the computational complexity of ADFs. Our results show that while ADFs are one level up in the polynomial hierarchy compared to AFs, there is a useful subclass of(More)
a r t i c l e i n f o a b s t r a c t Within the last decade, abstract argumentation has emerged as a central field in Artificial Intelligence. Besides providing a core formalism for many advanced argumentation systems, abstract argumentation has also served to capture several non-monotonic logics and other AI related principles. Although the idea of(More)
Within the area of computational models of argumentation, the instan-tiation-based approach is gaining more and more attention, not at least because meaningful input for Dung's abstract frameworks is provided in that way. In a nutshell, the aim of instantiation-based argumentation is to form, from a given knowledge base, a set of arguments and to identify(More)
Within the last decade, abstract argumentation has emerged as a central field in Artificial Intelligence. Besides serving as a core formalism for many advanced argumenta-tion systems, this is mainly due to the fact that abstract argumentation has been shown to capture several nonmonotonic logics and other AI related principles. Although the idea of abstract(More)
argumentation frameworks (AFs) provide the basis for various reasoning problems in the areas of Knowledge Representation and Artificial Intelligence. Efficient evaluation of AFs has thus been identified as an important research challenge. So far, implemented systems for evaluating AFs have either followed a straightforward reduction-based approach or been(More)