
Probability intervals [Moral] are an attractive tool for reasoning under uncertainty. Unlike belief functions, though, they lack a natural probability
transformation (such as the pignistic function for BFs) that could be used for decision making in a utility theory framework.
We propose the use
of the intersection probability, a transformation derived originally for belief functions in our geometric framework, as the most natural
such transformation. This outlines a novel decision making framework for probability intervals, analogous to the Transferable Belief Model for
belief functions.
