Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes
them be identified with the whole AI by many non-computer-scientists and non-technical …

Together with the disruptive development of modern sub-symbolic approaches to artificial
intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more …

Abstract Argumentation is a major topic in the study of Artificial Intelligence. Since the first
edition in 2015, advancements in solving (abstract) argumentation frameworks are assessed …

Abstract Semantics based on weak admissibility were recently introduced to overcome a
problem with self-defeating arguments that has not been solved for more than 25 years. The …

We employ graph convolutional networks for the purpose of determining the set of
acceptable arguments under preferred semantics in abstract argumentation problems. While …

Powerful formalisms for abstract argumentation have been proposed, among them abstract
dialectical frameworks (ADFs) that allow for a succinct and flexible specification of the …

We address the task of selecting the fastest algorithm, in terms of runtime, for determining
skeptical acceptance under preferred semantics in abstract argumentation frameworks out of …

Many recent studies of dynamics in formal argumentation within AI focus on the well-known
formalism of Dung's argumentation frameworks (AFs). Despite the usefulness of AFs in many …

An abstract argumentation framework is a directed graph such that the vertices of denote
abstract arguments and represents the attack relation between them. We present a new ad …

We address complex reasoning tasks in assumption-based argumentation (ABA) by
develo** dynamic programming algorithms based on tree-decompositions. As one of the …