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Professor Thierry Denoeux, University of Compiègne, France
We will start with a critical discussion about the concepts of “aleatory” and “epistemic” uncertainty. We will then review the two classical mathematical models of uncertain information: probabilities and sets (as exemplified by interval analysis), and proceed with two important extensions: fuzzy sets and possibility theory on the one hand, random sets and belief functions on the other hand. We will then introduce an even more general model based on random fuzzy sets, and argue for its relevance as a general approach to reasoning with epistemic uncertainty. As an illustration, we will demonstrate the application of this model to statistical prediction. Related publication: Thierry Denoeux, Belief functions induced by random fuzzy sets: a general framework for representing uncertain and fuzzy evidence, Fuzzy Sets and Systems, 2020, https://doi.org/10.1016/j.fss.2020.12.004.
Speaker biosketch
Thierry Denoeux is a Full Professor (Exceptional Class) with the Department of Information Processing Engineering at the University of Compiègne, France, and a senior member of the French Academic Institute (Institut Universitaire de France). His research interests concern reasoning and decision-making under uncertainty and, more generally, the management of uncertainty in intelligent systems. His main contributions are in the theory of belief functions with applications to statistical inference, pattern recognition, machine learning and information fusion. He has published more than 300 papers in this area. He is the editor-in-chief of the International Journal of Approximate Reasoning and the journal Array, and an associate editor of several journals including Fuzzy Sets and Systems and International Journal on Uncertainty, Fuzziness and Knowledge-Based Systems.
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