Abstract Answer Set Programming (ASP) is a well-known logic-based formalism that has
been used to model and solve a variety of AI problems. For several years, ASP …

Probabilistic reasoning, parameter learning, and most probable explanation inference for
answer set programming have recently received growing attention. They are only some of …

Answer set programming (ASP) is a popular declarative programming paradigm with a wide
range of applications in artificial intelligence. Oftentimes, when modeling an AI problem with …

Abstract Dung's abstract Argumentation Framework (AF) has emerged as a central
formalism for argumentation in AI. Preferences in AF allow to represent the comparative …

Abstract Answer Set Programming (ASP) is a paradigm for modeling and solving problems
for knowledge representation and reasoning. There are plenty of results dedicated to …

Recent developments on solvers for abstract argumentation frameworks (AFs) made them
capable to compute extensions for many semantics efficiently. However, for many input …

Abstract Argumentation frameworks (AFs) are a core formalism in the field of formal
argumentation. As most standard computational tasks regarding AFs are hard for the first or …

Efficient computation of hard reasoning tasks is a key issue in abstract argumentation. One
recent approach consists in defining approximate algorithms, ie methods that provide an …

We revisit the foundations of ranking semantics for abstract argumentation frameworks by
observing that most existing approaches are incompatible with classical extension-based …

Answer set programming (ASP) is a popular declarative programming paradigm with various
applications. Programs can easily have many answer sets that cannot be enumerated in …