Abstract
The complexity of the probabilistic counterparts of the verification and acceptance problems is investigated over probabilistic Abstract Argumentation Frameworks (prAAFs), in a setting more general
than the literature, where the complexity has been characterized only under independence between arguments/defeats.
The complexity of these problems is shown to depend on the semantics of the extensions, the way of encoding the prAAF, and the correlations between arguments/defeats.
In this regard, in order to study the impact of different correlations between arguments/defeats on the complexity, a new form of prAAF is introduced, called gen.
It is based on the well-known paradigm of world-set sets, and it allows the correlations to be easily distinguishable.
Keywords
- Uncertainty in AI: Uncertainty in AI
- Agent-based and Multi-agent Systems: Agreement Technologies: Argumentation
- Knowledge Representation and Reasoning: Computational Complexity of Reasoning
- Knowledge Representation and Reasoning: Computational Models of Argument
