This paper is concerned with the combination of argumentation with the Dempster-Shafer theory of evidence. In particular, we show how logical elements of evidence, associated with numerical degrees of belief, can be combined into arguments.

The Dempster Shafer theory of evidence is developed here in a very general setting First its symbolic or algebraic part is discussed as a body of arguments which contains an allocation of support and an allowment of possibility for each hypothesis It is shown how such bodies of arguments arise in the theory of hints and in assumption based reasoning in logic A rule of combination of bodies of a...

This paper responds to a number of criticisms of Dempster-Shafer theory made by Judea Pearl. He criticises Dempster-Shafer belief for not obeying the laws of Bayesian belief," however, these laws lead to well-known problems in the face of ignorance, and seem unreasonably restrictive. It is argued that it is not reasonable to expect a measure of belief to obey Pearl's sandwich principle. The sta...

Despite its huge potential in risk analysis, the Dempster–Shafer Theory of Evidence (DST) has not received enough attention in construction management. This paper presents a DST-based approach for structuring personal experience and professional judgment when assessing construction project risk. DST was innovatively used to tackle the problem of lacking sufficient information through enabling a...

Abstract A generalization of technique for establishing order preference by similarity to the ideal solution ( TOPSIS ) in intuitionistic fuzzy setting based on redefinition sets theory IFS framework Dempster-Shafer DST evidence is proposed. The use mathematical tools makes it possible avoid a set limitations and drawbacks revealed recently conventional Atanassov’s operational laws defined valu...

The paper presents a novel view of the Dempster-Shafer belief function as a measure of diversity in relational data bases. The Dempster rule of evidence combination corresponds to the join operator of the relational database theory. This rough-set based interpretation is qualitative in nature and can represent a number of belief function operators.

Uncertainty always exists in nature and real systems. It is known that probability has been used traditionally in modeling uncertainty. Since a belief function was proposed as an another type of measuring uncertainty, Dempster-Shafer theory (DST) has been widely studied and applied in diverse areas. Because of the advent of computer technology, the representation of human knowledge can be proce...