The Transferable Belief approach to the Theory of Evidence is based on the pignistic transform which, mapping belief functions to probability distributions, allows to make “precise” decisions on a set of disjoint hypotheses via classical utility theory. In certain scenarios, however, such as medical diagnosis, the need for an “imprecise” approach to decision making arises, in which sets of poss...

Belief revision and belief update are two of the most basic types of belief change operations. We need to select either revision or update when we accept new information into the current belief, however, such decision making has not been considered. In this paper, we propose a unified framework of revision and update based on state transition models that enable us to do such decision making. Th...

This paper extends the decision tree technique to an uncertain environment where the uncertainty is represented by belief functions as interpreted in the Transferable Belief Model (TBM). This so-called belief decision tree is a new classification method adapted to uncertain data. We will be concerned with the construction of the belief decision tree from a training set where the knowledge about...