Model Multiplicity (MM), also known as predictive multiplicity or the Rashomon Effect, refers
to a scenario where multiple, equally performing machine learning (ML) models may be …

Argumentation Frameworks (AFs) are a key formalism in AI research. Their semantics have
been investigated in terms of principles, which define characteristic properties in order to …

Many structured argumentation approaches proceed by constructing a Dung-style
argumentation framework (AF) corresponding to a given knowledge base. While a main …

In this paper, we explore the issue of inconsistency handling over prioritized knowledge
bases (KBs), which consist of an ontology, a set of facts, and a priority relation between …

Dealing with controversial information is an important issue in several application contexts.
Formal argumentation enables reasoning on arguments for and against a claim to decide on …

Abstract Argumentation is a process of evaluating and comparing sets of arguments.
Ranking-based semantics received a lot of attention recently. All of the semantics introduced …

Abstract Argumentation frameworks are a core formalism in the field of formal
argumentation, with several semantics being proposed in the literature. Among them …

Abstract Argumentation has been an important topic in knowledge representation, reasoning
and multi-agent systems during the last twenty years. In this paper, we propose a new …

In this paper, we consider argumentation frameworks with sets of attacking arguments
(SETAFs) due to Nielsen and Parsons, an extension of Dung's abstract argumentation …

In abstract argumentation, arguments jointly attacking single arguments is a well-understood
concept, captured by the established notion of SETAFs—argumentation frameworks with …