Keynote speaker

    Johannes P. Wallner
Institute of Software Technology, Faculty of Computer Science and Biomedical Engineering, TU Graz, Austria
Keynote title: Reasoning in Structured Argumentation: Assumption-based Argumentation and ASPIC+
Abstract: Research in computational argumentation, as a branch in Artificial Intelligence (AI), is dedicated to study representations of arguments and to develop automated argumentative reasoning. The subfield of structured argumentation comprises of several approaches, which describe how to perform rational and automated argumentative reasoning, usually based on rule-based knowledge bases. From such bases arguments, and relations among arguments, are instantiated. Subsequently, reasoning can be carried out on the constructed arguments, oftentimes without the need to consider the internal structure of these arguments. In this way, argumentation semantics drive the reasoning process on such abstracted arguments. In recent years, research on computational aspects, i.e., developing theoretical foundations, algorithmic approaches, and systems, for structured argumentation has gained significant traction in the research community. We give an overview of recent strands of research on two prominent structured argumentation formalisms: assumption-based argumentation (ABA) and ASPIC+. We look at issues and benefits arising from instantiation or explication of arguments, discuss complexity results and algorithms for reasoning in ABA and ASPIC+, and consider how incorporation of preferences changes the picture. We close with open issues and possible directions for future research.
Biography: Johannes P. Wallner is an assistant professor on a tenure-track at the Graz University of Technology, where he received his habilitation degree. Prior to his appointment, Wallner received his PhD and was a principle investigator at TU Wien, and was a post-doctoral researcher at the University of Helsinki. Wallner has provided foundational computational results to diverse fields in knowledge representation and reasoning (KR&R) including inconsistency measurement, belief change and computational social choice, and, with particular focus, computational argumentation.

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