Abstract

Abstract

Argumentation frameworks have been widely studied both in terms of formal properties they exhibit under different semantics and in terms of applications they can support. But where are argumentation frameworks coming from, and how can argumentation, a model-based approach to AI, beneficially integrate with the nowadays-much-widespread data-centric AI perspective? In this talk I will overview applications empowered by a variety of (extension-based and gradual) semantics for abstract and bipolar argumentation frameworks automatically obtained from data (including but not limited to text) and from logical rules. Some of these applications require the integration of argumentation and machine learning, and result in a mixed model-based and data-centric pipeline. For some applications, the semantics informs the definition of the frameworks rather than, as is conventionally the case, being enforced on frameworks a posteriori.

Bio

Francesca Toni is Professor in Computational Logic in the Department of Computing, Imperial College London, UK, and the funder and leader of the CLArg (Computational Logic and Argumentation) research group. Her research interests lie within the broad area of Knowledge Representation and Reasoning in Artificial Intelligence. She graduated, summa cum laude, in Computing at the University of Pisa, Italy, in 1990, and received her PhD in Computing in 1995, from Imperial College London. She has coordinated two EU projects, received funding from EPSRC and the EU, and awarded a Senior Research Fellowship from The Royal Academy of Engineering and the Leverhulme Trust. She is currently Technical Director of the ROAD2H EPSRC -funded project (www.road2h.org). She was a founding member of the steering committee of COMMA (COMputational Models of Argument) and participates routinely in the organisation of top events in AI (e.g. she is currently are chair of of IJCAI2019 and was programme co-chair of KR2018 ). She is, amongst other things, in the editorial board of Argument&Computation and of Artificial Intelligence.