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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

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

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

We first show that there are practical situations in for instance forensic and gambling settings, in which applying classical probability theory, that is, based on the axioms of Kolmogorov, is problematic. We then introduce and discuss…

Probability · Mathematics 2015-12-07 Timber Kerkvliet , Ronald Meester

In Dempster-Shafer belief theory, general beliefs are expressed as belief mass distribution functions over frames of discernment. In Subjective Logic beliefs are expressed as belief mass distribution functions over binary frames of…

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

We extend the notion of belief function to the case where the underlying structure is no more the Boolean lattice of subsets of some universal set, but any lattice, which we will endow with a minimal set of properties according to our…

Discrete Mathematics · Computer Science 2008-11-21 Michel Grabisch

With the desire to apply the Dempster-Shafer theory to complex real world problems where the evidential strength is often imprecise and vague, several attempts have been made to generalize the theory. However, the important concept in the…

Artificial Intelligence · Computer Science 2013-04-10 John Yen

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

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

Several authors have explained that the likelihood ratio measures the strength of the evidence represented by observations in statistical problems. This idea works fine when the goal is to evaluate the strength of the available evidence for…

Artificial Intelligence · Computer Science 2013-02-01 Paul-Andre Monney

The conditioning in the Dempster-Shafer Theory of Evidence has been defined (by Shafer \cite{Shafer:90} as combination of a belief function and of an "event" via Dempster rule. On the other hand Shafer \cite{Shafer:90} gives a…

Artificial Intelligence · Computer Science 2017-06-09 Andrzej Matuszewski , Mieczysław A. Kłopotek

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

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

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 describes a natural framework for rules, based on belief functions, which includes a repre- sentation of numerical rules, default rules and rules allowing and rules not allowing contraposition. In particular it justifies the use…

Artificial Intelligence · Computer Science 2013-04-05 Nic Wilson

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

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. Besides, it has been proven that the quantum theory…

Artificial Intelligence · Computer Science 2018-05-01 Fuyuan Xiao

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

Decision making is still an open issue in the application of Dempster-Shafer evidence theory. A lot of works have been presented for it. In the transferable belief model (TBM), pignistic probabilities based on the basic probability as-…

Artificial Intelligence · Computer Science 2014-06-09 Meizhu Li , Qi Zhang , Yong Deng

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
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