
We are also studying the problem of conditioning a belief function b with respect to an event A by geometrically projecting such belief function
onto the simplex associated with A in the belief space. Two different such simplices can be defined, as each belief function can be represented as
the vector of its basic probability values or the vector of its belief values. We show here that defining geometric conditional BFs by minimizing
Lp distances between b and the conditioning simplex in the mass space produces simple, elegant results with straightforward interpretations in terms
of degrees of belief. This opens the way to a systematic exploration of geometric conditioning in the belief space too, and the relationships of
these results with classical approaches to the problem.


Relevant papers:

Fabio Cuzzolin Geometric conditioning of belief functions Proceedings of the
First International Workshop on the Theory of Belief Functions Brest, Belgium, April 2010 


