A matrix approach for computing extensions of argumentation frameworks
This work provides a novel mathematical method for argumentation theory, addressing a computational bottleneck in AI reasoning systems.
The authors tackled the problem of computing all extensions in Dung's argumentation frameworks by introducing a matrix-based approach, which efficiently finds all extensions under given semantics and fully achieves the goal of computation.
The matrices and their sub-blocks are introduced into the study of determining various extensions in the sense of Dung's theory of argumentation frameworks. It is showed that each argumentation framework has its matrix representations, and the core semantics defined by Dung can be characterized by specific sub-blocks of the matrix. Furthermore, the elementary permutations of a matrix are employed by which an efficient matrix approach for finding out all extensions under a given semantics is obtained. Different from several established approaches, such as the graph labelling algorithm, Constraint Satisfaction Problem algorithm, the matrix approach not only put the mathematic idea into the investigation for finding out various extensions, but also completely achieve the goal to compute all the extensions needed.