Model Multiplicity (MM) arises when multiple, equally performing machine learning models
can be trained to solve the same prediction task. Recent studies show that models obtained …

In this paper, we study conditional preferences in abstract argumentation by introducing a
new generalization of Dung-style argumentation frameworks (AFs) called Conditional …

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

Dung's abstract argumentation frameworks (AFs) are a key formalism in AI research
nowadays. Claims are an inherent part of each argument; they substantially determine the …

Assumption-based argumentation (ABA) is a powerful defeasible reasoning formalism which
is based on the interplay of assumptions, their contraries, and inference rules. ABA with …

Abstract Qualitative Choice Logic (QCL) extends classical propositional formulas by a
connective called ordered disjunction that is used to express preferences. We translate QCL …

Evidence from studies, such as in science or medicine, often corresponds to conditional
probability statements. Furthermore, evidence can conflict, in particular when coming from …

Generalising the attack structure in argumentation frameworks (AFs) has been studied in
different ways. Most prominently, the binary attack relation of Dung frameworks has been …

The article develops model-theoretic methods for formalizing reasoning and argumentation.
An important application of these studies is the creation of intelligent assistants. One of the …

Abstract Model Multiplicity (MM) arises when multiple, equally performing machine learning
models can be trained to solve the same prediction task. Recent studies show that models …