Call for Papers (a one page CFP can be found here)

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 conference will provide opportunities to exchange ideas and present new results on the theory of belief functions and related areas such as random sets and possibility theory. Original contributions are solicited on theoretical aspects, including :
  • decision making,
  • combination rules,
  • continuous belief functions,
  • independence and graphical models,
  • statistical inference, etc.,

  • as well as on applications in various areas including, but not limited to :

  • data fusion,
  • pattern recognition,
  • clustering,
  • tracking,
  • data mining,
  • signal and image processing,
  • medical diagnosis,
  • business decision,
  • uncertainty in numerical models, etc.
Papers will be presented orally during the conference.

Deadlines for full paper submission can be found at IMPORTANT DATES.

All accepted papers will be published by Springer-Verlag in a volume of the series “Advances in Intelligent and Soft Computing” (indexed in ISI Proceedings, DBLP. Ulrich's, EI-Compendex, SCOPUS, Zentralblatt Math, MetaPress, Springerlink).

Authors of selected papers from the BELIEF 2012 conference will be invited to submit an extended version of their papers for possible inclusion in a special issue of the International Journal of Approximate Reasoning.