Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6857360 | Information Sciences | 2016 | 21 Pages |
Abstract
The aim is to provide a characterization of full conditional measures on a finite Boolean algebra, obtained as lower envelope of the extensions of a full conditional probability defined on another finite Boolean algebra. Such conditional measures are conditional belief functions defined by means of a generalized Bayesian conditioning rule relying on a linearly ordered class of belief functions. This notion of Bayesian conditioning for belief functions is compared with other well-known conditioning rules by looking for those conditional measures that can be seen as lower conditional probabilities.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Giulianella Coletti, Davide Petturiti, Barbara Vantaggi,