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When reasoning with uncertainty there are many situations where evidences are not only uncertain but their propositions may also be weakly specified in the sense that it may not be certain to which event a proposition is referring. It is…

Artificial Intelligence · Computer Science 2007-05-23 Johan Schubert

This paper explores belief inference in credal networks using Dempster-Shafer theory. By building on previous work, we propose a novel framework for propagating uncertainty through a subclass of credal networks, namely chains. The proposed…

Artificial Intelligence · Computer Science 2025-07-11 Marco Sangalli , Thomas Krak , Cassio de Campos

Dempster-Shafer theory of evidence is widely applied to uncertainty modelling and knowledge reasoning because of its advantages in dealing with uncertain information. But some conditions or requirements, such as exclusiveness hypothesis and…

Artificial Intelligence · Computer Science 2017-03-16 Xinyang Deng , Wen Jiang

In an earlier article [J. Schubert, On nonspecific evidence, Int. J. Intell. Syst. 8(6), 711-725 (1993)] we established within Dempster-Shafer theory a criterion function called the metaconflict function. With this criterion we can…

Artificial Intelligence · Computer Science 2007-05-23 Johan Schubert

A new entropy-like measure as well as a new measure of total uncertainty pertaining to the Dempster-Shafer theory are introduced. It is argued that these measures are better justified than any of the previously proposed candidates.

Artificial Intelligence · Computer Science 2013-03-25 George J. Klir , Behzad Parviz

Dempster/Shafer (D/S) theory has been advocated as a way of representing incompleteness of evidence in a system's knowledge base. Methods now exist for propagating beliefs through chains of inference. This paper discusses how rules with…

Artificial Intelligence · Computer Science 2013-04-10 Paul K. Black , Kathryn Blackmond Laskey

This is a working paper summarizing results of an ongoing research project whose aim is to uniquely characterize the uncertainty measure for the Dempster-Shafer Theory. A set of intuitive axiomatic requirements is presented, some of their…

Artificial Intelligence · Computer Science 2013-02-21 David Harmanec

This paper investigates the issues of combination and normalization of interval-valued belief structures within the framework of Dempster-Shafer theory of evidence. Existing approaches are reviewed and thoroughly analyzed. The advantages…

Artificial Intelligence · Computer Science 2020-11-30 Miao Qin , Yongchuan Tang

This paper investigates the use of Evidence Theory to enhance the training efficiency of object detection models by incorporating uncertainty into the feedback loop. In each training iteration, during the validation phase, Evidence Theory…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 M. Tahasanul Ibrahim , Rifshu Hussain Shaik , Andreas Schwung

In this chapter, we present and discuss a new generalized proportional conflict redistribution rule. The Dezert-Smarandache extension of the Demster-Shafer theory has relaunched the studies on the combination rules especially for the…

Artificial Intelligence · Computer Science 2008-12-18 Arnaud Martin , Christophe Osswald

This paper describes recent work on an ongoing project in medical diagnosis at the University of Guelph. A domain on which experts are not very good at pinpointing a single disease outcome is explored. On-line medical data is available over…

Artificial Intelligence · Computer Science 2013-04-05 Mary McLeish , P. Yao , T. Stirtzinger

In the canonical examples underlying Shafer-Dempster theory, beliefs over the hypotheses of interest are derived from a probability model for a set of auxiliary hypotheses. Beliefs are derived via a compatibility relation connecting the…

Artificial Intelligence · Computer Science 2013-04-11 Kathryn Blackmond Laskey

Dempster-Shafer structure is effective in classical settings for connecting set-valued hypotheses and representing structured ignorance, yet its practical use is limited by combination growth over focal sets and high conflict management. We…

Artificial Intelligence · Computer Science 2025-10-21 Qianli Zhou , Hao Luo , Lipeng Pan , Yong Deng , Eloi Bosse

Within the framework of evidence theory, the confidence functions of different information can be combined into a combined confidence function to solve uncertain problems. The Dempster combination rule is a classic method of fusing…

Statistical Finance · Quantitative Finance 2021-08-09 Tianxiang Zhan , Fuyuan Xiao

One important obstacle in applying Dempster-Shafer Theory (DST) is its relationship to frequencies. In particular, there exist serious difficulties in finding factorizations of belief functions from data. In probability theory…

Artificial Intelligence · Computer Science 2018-12-17 Andrzej Matuszewski , Mieczysław A. Kłopotek

Partial correlation coefficients are widely applied in the social sciences to evaluate the relationship between two variables after accounting for the influence of others. In this article, we present Bayes Factor Functions (BFFs) for…

Methodology · Statistics 2026-04-16 Saptati Datta

We develop our interpretation of the joint belief distribution and of evidential updating that matches the following basic requirements: * there must exist an efficient method for reasoning within this framework * there must exist a clear…

Artificial Intelligence · Computer Science 2017-04-14 Mieczysław Kłopotek

It is explored that available credible evidence fusion schemes suffer from the potential inconsistency because credibility calculation and Dempster's combination rule-based fusion are sequentially performed in an open-loop style. This paper…

Artificial Intelligence · Computer Science 2025-04-08 Chaoxiong Ma , Yan Liang , Huixia Zhang , Hao Sun

We suggest novel correlation coefficients which equal the maximum correlation for a class of bivariate Lancaster distributions while being only slightly smaller than maximum correlation for a variety of further bivariate distributions. In…

Methodology · Statistics 2024-05-01 Hajo Holzmann , Bernhard Klar

In the current versions of the Dempster-Shafer theory, the only essential restriction on the validity of the rule of combination is that the sources of evidence must be statistically independent. Under this assumption, it is permissible to…

Artificial Intelligence · Computer Science 2013-04-12 Lotfi Zadeh , Anca Ralescu