From Comparative Degrees of Belief to Conditional Measures

Aim of this paper is to give a contribute to the discussion about the "best" definition of conditional model for plausibilty functions and its subclass of the possibility functions. We propose to use the framework of the theory of measurements: by studying the comparative structure underling different conditional models. This approach gives an estimate of the "goodness" and "effectiveness" of the model, by pointing out the rules necessarily accepted by the user. Moreover, the results related to the characterization of comparative degree of belief by means conditional uncertainty measures can be used in decision theory. They are in fact necessary when we need a model for a decision maker interested in choosing by taking into account, at the same moment, different scenarios.