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Related papers: Using Dempster-Shafer Theory in Knowledge Represen…

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The issue of confidence factors in Knowledge Based Systems has become increasingly important and Dempster-Shafer (DS) theory has become increasingly popular as a basis for these factors. This paper discusses the need for an empirical…

Artificial Intelligence · Computer Science 2013-04-15 John F. Lemmer

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

Dempster-Shafer theory is widely applied to uncertainty modelling and knowledge reasoning due to its ability of expressing uncertain information. However, some conditions, such as exclusiveness hypothesis and completeness constraint, limit…

Artificial Intelligence · Computer Science 2014-05-13 Xinyang Deng , Yong Deng

The Dempster-Shafer theory of evidence has been used intensively to deal with uncertainty in knowledge-based systems. However the representation of uncertain relationships between evidence and hypothesis groups (heuristic knowledge) is…

Artificial Intelligence · Computer Science 2013-03-25 Weiru Liu , John G. Hughes , Michael F. McTear

In this paper we present a methodology and discuss some implementation issues for a project on statistical/expert approach to data analysis and knowledge acquisition. We discuss some general assumptions underlying the project. Further, the…

Artificial Intelligence · Computer Science 2017-05-24 M. Michalewicz , S. T. Wierzchoń , M. A. Kłopotek

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

Dempster-Shafer evidence theory has been widely used in various fields of applications, because of the flexibility and effectiveness in modeling uncertainties without prior information. However, the existing evidence theory is insufficient…

Artificial Intelligence · Computer Science 2019-06-28 Fuyuan Xiao

Mathematical Theory of Evidence called also Dempster-Shafer Theory (DST) is known as a foundation for reasoning when knowledge is expressed at various levels of detail. Though much research effort has been committed to this theory since its…

Artificial Intelligence · Computer Science 2017-07-14 Mieczysław A. Kłopotek

By analyzing the relationships among chance, weight of evidence and degree of beliefwe show that the assertion "probability functions are special cases of belief functions" and the assertion "Dempster's rule can be used to combine belief…

Artificial Intelligence · Computer Science 2013-02-28 Pei Wang

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

We discuss the Dempster-Shafer theory of evidence. We introduce a concept of monotonicity which is related to the diminution of the range between belief and plausibility. We show that the accumulation of knowledge in this framework exhibits…

Artificial Intelligence · Computer Science 2013-04-08 Ronald R. Yager

We formulate Dempster Shafer Belief functions in terms of Propositional Logic using the implicit notion of provability underlying Dempster Shafer Theory. Given a set of propositional clauses, assigning weights to certain propositional…

Artificial Intelligence · Computer Science 2013-04-08 Gregory M. Provan

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

A control strategy for expert systems is presented which is based on Shafer's Belief theory and the combination rule of Dempster. In contrast to well known strategies it is not sequentially and hypotheses-driven, but parallel and self…

Artificial Intelligence · Computer Science 2013-03-26 Kerstin Schill , Ernst Poppel , Christoph Zetzsche

In this paper, we generalize the basic notions and results of Dempster-Shafer theory from predicates to formal concepts. Results include the representation of conceptual belief functions as inner measures of suitable probability functions,…

Artificial Intelligence · Computer Science 2021-05-19 Sabine Frittella , Krishna Manoorkar , Alessandra Palmigiano , Apostolos Tzimoulis , Nachoem M. Wijnberg

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

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

Efficient modeling of uncertain information in real world is still an open issue. Dempster-Shafer evidence theory is one of the most commonly used methods. However, the Dempster-Shafer evidence theory has the assumption that the hypothesis…

Artificial Intelligence · Computer Science 2014-05-14 Yong Deng

As a generalization of Dempster-Shafer theory, D number theory provides a framework to deal with uncertain information with non-exclusiveness and incompleteness. However, some basic concepts in D number theory are not well defined. In this…

Artificial Intelligence · Computer Science 2019-12-03 Xinyang Deng

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
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