Title
On rejected arguments and implicit conflicts: The hidden power of argumentation semantics.
Abstract
Abstract argumentation frameworks (afs) are one of the most studied formalisms in AI and are formally simple tools to model arguments and their conflicts. The evaluation of an af yields extensions (with respect to a semantics) representing alternative acceptable sets of arguments. For many of the available semantics two effects can be observed: there exist arguments in the given af that do not appear in any extension (rejected arguments); there exist pairs of arguments that do not occur jointly in any extension, albeit there is no explicit conflict between them in the given af (implicit conflicts). In this paper, we investigate the question whether these situations are only a side-effect of particular afs, or whether rejected arguments and implicit conflicts contribute to the expressiveness of the actual semantics. We do so by introducing two subclasses of afs, namely compact and analytic frameworks. The former class contains afs that do not contain rejected arguments with respect to a semantics at hand; afs from the latter class are free of implicit conflicts for a given semantics. Frameworks that are contained in both classes would be natural candidates towards normal forms for afs since they minimize the number of arguments on the one hand, and on the other hand maximize the information on conflicts, a fact that might help argumentation systems to evaluate afs more efficiently. Our main results show that under stable, preferred, semi-stable, and stage semantics neither of the classes is able to capture the full expressive power of these semantics; we thus also refute a recent conjecture by Baumann et al. on implicit conflicts. Moreover, we give a detailed complexity analysis for the problem of deciding whether an af is compact, resp. analytic. Finally, we also study the signature of these subclasses for the mentioned semantics and shed light on the question under which circumstances an arbitrary framework can be transformed into an equivalent compact, resp. analytic, af.
Year
DOI
Venue
2016
10.1016/j.artint.2016.09.004
Artificial Intelligence
Keywords
Field
DocType
Abstract argumentation,Nonmonotonic reasoning,Complexity
Discrete mathematics,Computer science,Argumentation theory,Theoretical computer science,Non-monotonic logic,Artificial intelligence,Rotation formalisms in three dimensions,Expressive power,Conjecture,Argumentation semantics,Semantics,Expressivity
Journal
Volume
Issue
ISSN
241
1
0004-3702
Citations 
PageRank 
References 
1
0.34
20
Authors
6
Name
Order
Citations
PageRank
Ringo Baumann122620.39
Wolfgang Dvorák227124.57
Thomas Linsbichler3449.17
Christof Spanring4153.22
Hannes Strass519422.50
Stefan Woltran61603121.99