Support in Abstract Argumentation
Proceedings of the 2010 conference on Computational Models of Argument: Proceedings of COMMA 2010
AFRA: Argumentation framework with recursive attacks
International Journal of Approximate Reasoning
Bipolarity in argumentation graphs: towards a better understanding
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
Argumentation frameworks with necessities
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
Generalizing naive and stable semantics in argumentation frameworks with necessities and preferences
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
A logic of argumentation for specification and verification of abstract argumentation frameworks
Annals of Mathematics and Artificial Intelligence
Modelling defeasible and prioritized support in bipolar argumentation
Annals of Mathematics and Artificial Intelligence
A socio-cognitive model of trust using argumentation theory
International Journal of Approximate Reasoning
Argumentation theoretic foundations for abstract dependence networks
AT'13 Proceedings of the Second international conference on Agreement Technologies
Coalitions of Arguments: An Approach with Constraint Programming
Fundamenta Informaticae - Special Issue on the Italian Conference on Computational Logic: CILC 2011
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Bipolar argumentation frameworks enable to represent two kinds of interaction between arguments: support and conflict. In this paper, we turn a bipolar argumentation framework into a meta-argumentation framework where conflicts occur between sets of arguments, characterized as coalitions of supporting arguments. So, Dung's well-known semantics can be used on this meta-argumentation framework to select the acceptable arguments. © 2009 Wiley Periodicals, Inc. This article is an extended version of a paper accepted for CMNA Workshop (Computational Models of Natural Arguments), which has been published in January 2007. This extension concerns algorithms, complexity results, and some new definitions and properties.