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Related papers: A Defect in Dempster-Shafer Theory

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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

We revisit Zadeh's notion of "evidence of the second kind" and show that it provides the foundation for a general theory of epistemic random fuzzy sets, which generalizes both the Dempster-Shafer theory of belief functions and possibility…

Artificial Intelligence · Computer Science 2022-02-17 Thierry Denoeux

The combination of evidence in Dempster-Shafer theory is compared with the combination of evidence in probabilistic logic. Sufficient conditions are stated for these two methods to agree. It is then shown that these conditions are minimal…

Artificial Intelligence · Computer Science 2013-04-11 Daniel Hunter

This paper is concerned with the apparent greatest weakness of the Mathematical Theory of Evidence (MTE) of Shafer \cite{Shafer:76}, which has been strongly criticized by Wasserman \cite{Wasserman:92ijar}. Weaknesses of Shafer's proposal…

Artificial Intelligence · Computer Science 2018-11-13 Mieczysław Kłopotek

Dempster-Shafer's model aims at quantifying degrees of belief But there are so many interpretations of Dempster-Shafer's theory in the literature that it seems useful to present the various contenders in order to clarify their respective…

Artificial Intelligence · Computer Science 2013-04-05 Philippe Smets

When we merge information in Dempster-Shafer Theory (DST), we are faced with anomalous behavior: agents with equal expertise and credibility can have their opinion disregarded after resorting to the belief combination rule of this theory.…

Artificial Intelligence · Computer Science 2024-08-20 Francisco Aragão , João Alcântara

Dempster-Shafer theory is widely applied in uncertainty modelling and knowledge reasoning due to its ability of expressing uncertain information. A distance between two basic probability assignments(BPAs) presents a measure of performance…

Artificial Intelligence · Computer Science 2014-04-15 Meizhu Li , Qi Zhang , Xinyang Deng , Yong Deng

The problem of combining beliefs in the Dempster-Shafer belief theory has attracted considerable attention over the last two decades. The classical Dempster's Rule has often been criticised, and many alternative rules for belief combination…

Artificial Intelligence · Computer Science 2007-05-23 Audun Josang

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

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

The paper presents a novel view of the Dempster-Shafer belief function as a measure of diversity in relational data bases. It is demonstrated that under the interpretation The Dempster rule of evidence combination corresponds to the join…

Artificial Intelligence · Computer Science 2017-04-11 Mieczysław A. Kłopotek , Sławomir T. Wierzchoń

Evidential reasoning in expert systems has often used ad-hoc uncertainty calculi. Although it is generally accepted that probability theory provides a firm theoretical foundation, researchers have found some problems with its use as a…

Artificial Intelligence · Computer Science 2013-04-15 Robert Fung , Chee Yee Chong

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

The Dempster--Shafer (DS) theory is a powerful tool for probabilistic reasoning based on a formal calculus for combining evidence. DS theory has been widely used in computer science and engineering applications, but has yet to reach the…

Methodology · Statistics 2010-11-04 Ryan Martin , Jianchun Zhang , Chuanhai Liu

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

We first discuss certain problems with the classical probabilistic approach for assessing forensic evidence, in particular its inability to distinguish between lack of belief and disbelief, and its inability to model complete ignorance…

Probability · Mathematics 2017-02-02 Timber Kerkvliet , Ronald Meester

The computational complexity of reasoning within the Dempster-Shafer theory of evidence is one of the main points of criticism this formalism has to face. To overcome this difficulty various approximation algorithms have been suggested that…

Artificial Intelligence · Computer Science 2013-02-18 Mathias Bauer

This paper examines the concept of a combination rule for belief functions. It is shown that two fairly simple and apparently reasonable assumptions determine Dempster's rule, giving a new justification for it.

Artificial Intelligence · Computer Science 2013-03-08 Nic Wilson

Inappropriate use of Dempster's rule of combination has led some authors to reject the Dempster-Shafer model, arguing that it leads to supposedly unacceptable conclusions when defaults are involved. A most classic example is about the…

Artificial Intelligence · Computer Science 2013-04-05 Philippe Smets , Yen-Teh Hsia

To develop an approach to utilizing continuous statistical information within the Dempster- Shafer framework, we combine methods proposed by Strat and by Shafero We first derive continuous possibility and mass functions from…

Artificial Intelligence · Computer Science 2013-04-12 Pascal Fua