This chapiter of a collective book is dedicated to classical decision models under uncertainty, i.e. under situations where events do not have "objective" probabilities with which the Decision Marker agrees. We present successively the two main theories, their axiomatic, the interpretation and...

We study the Full Bayesian Updating rule for convex capacities. Following a route suggested by Jaffray (1992), we define some properties one may want to impose on the updating process, and identify the classes of (convex and strictly positive) capacities that satisfy these properties for the...

This article studies situations in which information is ambiguous and only part of it can be probably. It is shown that the information can be modeled through belief functions if and only if the nonprobabilizable information is subject to the principle of complete ignorance. Next the...