Abstract Argumentation Frameworks with Marginal Probabilities
Abstract Argumentation Frameworks with Marginal Probabilities
Bettina Fazzinga, Sergio Flesca, Filippo Furfaro
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
Main Track. Pages 2613-2619.
https://doi.org/10.24963/ijcai.2022/362
In the context of probabilistic AAFs, we intro-
duce AAFs with marginal probabilities (mAAFs)
requiring only marginal probabilities of argu-
ments/attacks to be specified and not relying on the
independence assumption. Reasoning over mAAFs
requires taking into account multiple probability
distributions over the possible worlds, so that the
probability of extensions is not determined by a
unique value, but by an interval. We focus on the
problems of computing the max and min probabil-
ities of extensions over mAAFs under Dung’s se-
mantics, characterize their complexity, and provide
closed formulas for polynomial cases.
Keywords:
Knowledge Representation and Reasoning: Argumentation
Agent-based and Multi-agent Systems: Agreement Technologies: Argumentation
Knowledge Representation and Reasoning: Computational Complexity of Reasoning