An interval-valued utility theory for decision making with Dempster-Shafer belief functions

Uncertain Decision Making with Dempster-Shafer Theory

We develop a new approach for decision making with Dempster-Shafer theory of evidence by using uncertain information represented in the form of interval numbers. We suggest the use of different types of uncertain aggregation operators in the problem. Then, we obtain new aggregation operators such as the belief structure uncertain ordered weighted averaging (BSUOWA) operator and the BS uncertain...

An Alternative to Outward Propagation for Dempster-Shafer Belief Functions

Given several Dempster-Shafer belief functions, the framework of valuation networks describes an efficient method for computing the marginal of the combined belief function. The computation is based on a message passing scheme in a Markov tree where after the selection of a root node an inward and an outward propagation can be distinguished. In this paper it will be shown that outward propagati...

Classic Works of the Dempster-Shafer Theory of Belief Functions

The validity of Dempster-Shafer belief functions

This reply to papers by Pearl and Shafer focuses on two issues underlying the debate on the validity o f using Dempster-Shafer theory, namely the requirement of a process-independent semantics and the a priori need for multiple uncertainty calculi. Pearl shows deficiencies of Dempster-Shafer theory in dealing with several instances o f commonsense reasoning in a process-independent manner. Alth...

Linguistic Decision Making Using Dempster-shafer Theory of Evidence

We study different approaches for decision making with linguistic information. We describe some basic linguistic aggregation operators. We then analyze the problem of linguistic decision making with Dempster-Shafer (D-S) belief structure. We suggest the use of different types of linguistic aggregation operators in the D-S framework such as the linguistic ordered weighted averaging (LOWA) operat...