The context model: An integrating view of vagueness and uncertainty

Abstract

The problem of handling vagueness and uncertainty as two different kinds of partial ignorance has become a major issue in several fields of scientific research. Currently the most popular approaches are Bayes theory, Shafer's evidence theory, the transferable belief model, and the possibility theory with its relationships to fuzzy sets. Since the justification of some of the mentioned theories has not been clarified for a long time, some criticism on these models is still pending. For that reason we have developed a model of vagueness and uncertainty—called the context model—that provides a formal environment for the comparison and semantic foundation of the referenced theories. In this paper we restrict ourselves to the presentation of basic ideas keyed to the interpretation of Bayes theory and the Dempster-Shafer theory within the context model. Furthermore the context model is applied to show a direct comparison of these two approaches based on the well-known spoiled sandwich effect, the three prisoners problem, and the unreliable alarm paradigm.