We discuss the use of the fuzzy measure for representing information about uncertain variables. We describe the relationship between the fuzzy measure and the Dempster-Shafer belief structure. A method for generating the fuzzy measures associated with a D-S belief structure is described. We discuss the use of the Shapley index as a means for providing an entropy for fuzzy measures. We introduce...

We construct the universal type structure for conditional probability systems without any topological assumption, namely a type structure that is terminal, belief-complete, and non-redundant. In particular, in order to obtain the belief-completeness in a constructive way, we extend the work of Meier [An Infinitary Probability Logic for Type Spaces. Israel Journal of Mathematics, 192, 1–58] by p...

We propose a database model that allows users to annotate data with belief statements. Our motivation comes from scientific database applications where a community of users is working together to assemble, revise, and curate a shared data repository. As the community accumulates knowledge and the database content evolves over time, it may contain conflicting information and members can disagree...

This paper presents a comparison of two architectures for belief propagation in evidential networks, namely the binary join tree using joint belief functions [9] and the modified binary join tree using conditional belief functions [2]. This comparison is done from the perspective of graphical structure, messagepassing scheme, computational efficiency, storage efficiency, and complexity analysis...

Belief propagation algorithms for constraint satisfaction problems by Elitza Nikolaeva Maneva Doctor of Philosophy in Computer Science and the Designated Emphasis in Communication, Computation, and Statistics University of California, Berkeley Professor Alistair Sinclair, Chair We consider applications of belief propagation algorithms to Boolean constraint satisfaction problems (CSPs), such as ...

TOPSIS is one of the major techniques in dealing with multiple criteria decision making (MCDM) problems, and Belief Structure (BS) model and Fuzzy BS model have been used successfully for uncertain MCDM with incompleteness, impreciseness or ignorance. In this paper, the TOPSIS method with Fuzzy BS model is proposed to solve Group Belief MCDM problems. Firstly, the Group Belief MCDM problem is s...

We propose a frame structure that is augmented with belief functions to model knowledge in a spoken dialog system. In addition we propose methods to combine belief functions in the network, and operations on the network to support a dialog manager. We show how our Belief Augmented Frames framework can be used to manage a spoken dialog system, and give a simple example on how knowledge can be re...