An Extension-Based Argument-Ranking Semantics: Social Rankings in Abstract Argumentation Long Version
This work addresses a specific problem in computational argumentation for researchers in AI and logic, presenting an incremental extension of existing semantics.
The paper tackles the problem of ranking arguments in abstract argumentation by introducing a new family of semantics that refines classifications into skeptically accepted, credulously accepted, and rejected arguments, using social ranking functions to achieve this refinement.
In this paper, we introduce a new family of argument-ranking semantics which can be seen as a refinement of the classification of arguments into skeptically accepted, credulously accepted and rejected. To this end we use so-called social ranking functions which have been developed recently to rank individuals based on their performance in groups. We provide necessary and sufficient conditions for a social ranking function to give rise to an argument-ranking semantics satisfying the desired refinement property.