Within the last decade, abstract argumentation has emerged as a central field in Artificial
Intelligence. Besides providing a core formalism for many advanced argumentation systems …

There exists a gap between visualization design guidelines and their application in
visualization tools. While empirical studies can provide design guidance, we lack a formal …

We introduce a new flexible paradigm of grounding and solving in Answer Set Programming
(ASP), which we refer to as multi-shot ASP solving, and present its implementation in the …

We present NeurASP, a simple extension of answer set programs by embracing neural
networks. By treating the neural network output as the probability distribution over atomic …

Answer Set Programming (ASP) is a declarative problem solving approach, initially tailored
to modeling problems in the area of Knowledge Representation and Reasoning (KRR) …

We present the new ASP system clingo 4. Unlike its predecessors, being mere monolithic
combinations of the grounder gringo with the solver clasp, the new clingo 4 series offers …

We introduce an approach to computing answer sets of logic programs, based on concepts
successfully applied in Satisfiability (SAT) checking. The idea is to view inferences in …

Algorithm selection (AS) techniques-which involve choosing from a set of algorithms the one
expected to solve a given problem instance most efficiently-have substantially improved the …

Probabilistic Logic Programming extends Logic Programming by enabling the
representation of uncertain information by means of probability theory. Probabilistic Logic …

Recent progress in both AI and robotics have enabled the development of general purpose
robot platforms that are capable of executing a wide variety of complex, temporally extended …