In this paper, the modal logic interpretation of plausibility and belief measures on an arbitrary universe of discourse, as proposed by Harmanec et al., is further developed by employing notions from set-valued analysis. In a model of modal logic, a multivalued mapping is constructed from the accessibility relation and a mapping determined by the value assignment function. This multivalued mapp...

This paper presents an event recognition framework, based on Dempster-Shafer theory, that combines evidence of events from low-level computer vision analytics. The proposed method employing evidential network modelling of composite events, is able to represent uncertainty of event output from low level video analysis and infer high-level events with semantic meaning along with degrees of belief...

This paper compares two formalisms for uncertain inference, Kyburg's Combinatorial Semantics and Dempster-Shafer belief function theory, on the basis of an example from the domain of medical diagnosis. I review Shafer's example about the imaginary disease ploxoma and show how it would be represented in Combinatorial Semantics. I conclude that belief function theory has a qualitative advantage b...

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...

One of the problems usually discussed in autonomous mobile robot navigation is how to build a map of the environment where the robot is navigating. In the case of indoor navigation, a suitable method to do this mapping is the fusion of the data that are gathered from the several sensors, which are mounted on the robot. Here, a mobile robot equipped just with range finding sensors has been suppo...

This paper describes a theory of reasoning about uncertainly, based on a representation of state'i of certainly called endorsements (see Cohen and Grinberg, 1983, for a more detailed discussion of the theory.) The theory of endorsements is an alternative to numerical methods for reasoning about uncertainty, such as subjective Bayesian methods (Shortliffe and Buchanan, 1975; Duda, Hart, and Nils...

Correctly modelling and reasoning with uncertain information from heterogeneous sources in large-scale systems is critical when the reliability is unknown and we still want to derive adequate conclusions. To this end, context-dependent merging strategies have been proposed in the literature. In this paper we investigate how one such context-dependent merging strategy (originally defined for pos...

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...

In this note, we argue that the axiomatic requirement of range to the measure of aggregated total uncertainty (ATU) in Dempster-Shafer theory is not reasonable.