The latest developments in Markov models’ theory and their corresponding computational techniques have opened new rooms for image and signal modeling. In particular, the use of Dempster–Shafer theory of evidence within Markov models has brought some keys to several challenging difficulties that the conventional hidden Markov models cannot handle. These difficulties are concerned mainly with two...

We study the problem of decision making with Dempster-Shafer belief structure. We analyze the previous work developed by Yager about using the ordered weighted averaging (OWA) operator in the aggregation of the Dempster-Shafer decision process. We discuss the possibility of aggregating with an ascending order in the OWA operator for the cases where the smallest value is the best result. We sugg...

We revisit Zadeh's notion of "evidence the second kind" and show that it provides foundation for a general theory epistemic random fuzzy sets, which generalizes both Dempster-Shafer belief functions possibility theory. In this perspective, deals with generated by while induced sets. The more allows us to represent combine evidence is uncertain fuzzy. demonstrate application formalism statistica...

We formulate Dempster Shafer Belief functions in terms of Propositional Logic, using the im­ plicit notion of provability underlying Demp­ ster Shafer Theory. The assignment of weights to the propositional literals enables the Belief functions to be explicitly computed using Net­ work Reliability techniques. Also, the updat­ ing of Belief functions using Dempster's Rule of Combination correspon...

The emergence of expert systems as one of the major areas of activity within AI has resulted in a rapid growth of interest within the AI community in issues relating to the management of uncertainty and evidential reasoning. During the past two years, in particular, the Dempster-Shafer theory of evidence has att,ract,ed considerable attention as a promising method of dealing with some of the ba...

Efficient modeling of uncertain information in real world is still an open issue. Dempster-Shafer evidence theory is one of the most commonly used methods. However, the Dempster-Shafer evidence theory has the assumption that the hypothesis in the framework of discernment is exclusive of each other. This condition can be violated in real applications, especially in linguistic decision making sin...

The initial work introducing Dempster-Shafer (D-S) theory is found in Dempster (1967) and Shafer (1976). Since its introduction the very name causes confusion, a more general term often used is belief functions (both used intermittently here). Nguyen (1978) points out, soon after its introduction, that the rudiments of D-S theory can be considered through distributions of random sets. More furt...

This paper suggests a new interpretation of the Dempster-Shafer theory in terms of probabilistic interpretation of plausibility. A new rule of combination of independent evidence is shown and its preservation of interpretation is demonstrated.

An evidential reasoning mechanism based on the Dempster-Shafer theory of evidence is introduced. Its performance in real-world image analysis is compared with other mechanisms based on the Bayesian formalism and a simple weight combination method.