Programme

Conférences invitées

Florence Dupin de Saint-Cyr

Stories and belief change
In the Knowledge Representation and Reasoning subfield of artificial intelligence, theories of belief change have had a great impact. Research in this area focuses on the properties of operators that allow us to take into account the evolution of knowledge as new information becomes available. In this context, how can we model the evolution of a listener's beliefs as he or she listens to a story? A story can be seen as a sequence of logical formulas indexed by instants, which can be apprehended as a whole in order to draw conclusions linked to the causality of events, or as a sequence of successive revisions of an agent's beliefs by the information that arrives along the way. With belief change tools, it is then possible to characterize some useful ingredients in storytelling such as surprise and incongruity.
 
Biographie
Florence Dupin de Saint-Cyr  has been lecturer at Toulouse Paul Sabatier University since 2005 and led  the ADRIA (Argumentation, Décision, Raisonnement (reasoning), Incertitude (uncertainty),
Apprentissage (learning)) team at IRIT from 2019 to 2024. She is currently full-time researcher for one-year at the lab-STICC laboratory in Brest. Florence Dupin de Saint-Cyr's research focuses on knowledge representation and the formalization of reasoning, in particular reasoning about change in the presence of imperfect information (incomplete, uncertain, inconsistent). She has worked on defeasible reasoning, logic-based and abstract argumentation, persuasion dialogues,  fallacies, bounded rationality,  explainable reinforcement learning. These works use logical or mathematical frameworks like graph and uncertainty theories. She has worked with more than thirty co-authors covering a large spectrum of the research in artificial intelligence. Her seminal article about change in abstract argumentation is cited 200 times. She was co-program chair of the 15th international conference en scalable uncertainty management SUM’2022 and president of the doctoral consortiums of ICAART’2015 and ICAART’2014.
 

Christophe Labreuche

 

Vu-Linh Nguyen

Uncertainty modeling/quantification and its applications in machine learning

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