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.

In 2012 alone, more than 300 papers on belief functions and their applications have been published worldwide. The ambition of the series of International Conferences on Belief Functions - BELIEF - is to bring together the large and expanding community of mathematicians, statisticians, computer scientists, engineers, economists and practitioners which work on the theoretical foundations of belief calculus or its application to all fields of applied science.

This 3rd edition, in particular, aims at more closely involving in the community the many specialists of other fields which use belief functions in their daily work, improving the overall visibility of the field by pushing towards a more coalesced and tightly connected community, and reaching out towards the sibling fields of uncertainty theory, Bayesian reasoning, imprecise probability and fuzzy theory.

The conference will provide opportunities to exchange ideas and present new results on both the theory and applications of belief functions and related areas such as random sets, imprecise probability and possibility theory.
Original contributions are solicited on theoretical aspects, including:

- decision making
- combination rules
- conditioning
- continuous belief functions
- independence and graphical models
- statistical inference
- geometry and distance metrics
- mathematical foundations
- computational frameworks

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

- data and information fusion
- pattern recognition
- machine learning and clustering
- tracking and data association
- data mining
- signal and image processing
- computer vision
- medical diagnosis
- business decision
- risk analysis
- engineering and environment
- climatic change

Papers will be presented orally during the conference in a single track session, or in poster sessions.