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CALL FOR PARTICIPATION : REGISTRATION ONLINE
BFAS Spring School on Belief Functions Theory and
Applications
Carthage, Tunisia, May 20-24, 2013
http://www.bfasociety.org/
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The theory of belief functions represents a new approach
devised to model and manage imprecise information in
Artificial and Computational Intelligence. The theory of
belief functions also referred to as evidence theory or
Dempster-Shafer theory, was first introduced by Arthur P.
Dempster in the context of statistical inference, and was
later developed by Glenn Shafer as a general framework for
modeling epistemic uncertainty. These early contributions
have been the starting points of many important
developments, including the Transferable Belief Model and
the Theory of Hints. The theory of belief functions is now
well established as a general framework for reasoning with
uncertainty, and has well understood connections to other
frameworks such as probability, possibility and imprecise
probability theories. This theoretical framework has a broad
field of application, including information fusion, pattern
recognition, auditing, etc.
The second BFAS spring school will take place at IHEC in the
historical and magnificent city of Carthage in Tunisia. The
aim of this spring school is to promote this theory and to
introduce interested students and researchers to the basics
of belief functions, both theoretical and applied. The
school is organized into several lectures given by
international experts. They will bring both theoretical and
practical backgrounds, in a friendly environment favoring
interaction between participants. Part of the time will be
devoted to practical work of real-world case studies.
SPEAKERS:
- Boutheina Ben Yaghlane (Tunisia)
- Thierry Denoeux (France)
- Didier Dubois (France)
- Zied Elouedi (Tunisia)
- Sylvie Le Hégarat-Mascle (France)
- Weiru Liu (United Kingdom)
- Arnaud Martin (France)
- Hung Nguyen (USA and Thailand)
- Rajendra Srivastava (USA)
CO-DIRECTORS OF THE SCHOOL
Boutheina Ben Yaghlane (Tunisia)
Khaled Mellouli (Tunisia)