Results 281 to 290 of about 1,058,148 (324)

Information fusion and decision-making using belief functions : application to therapeutic monitoring of cancer

, 2017
Chunfeng Lian
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The normative representation of quantified beliefs by belief functions

Artificial Intelligence, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Consonant approximations of belief functions

International Journal of Approximate Reasoning, 1990
Based on a recently introduced definition of inclusion between random sets, a general notion of approximation of a belief function by some other set-function is introduced. Viewing a fuzzy set as a consonant random set, it is shown how to construct fuzzy sets that may act as approximations of belief functions. Two kinds of approximations are considered:
Didier Dubois, Henri Prade
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Analyzing belief function networks with conditional beliefs

2011 11th International Conference on Intelligent Systems Design and Applications, 2011
The success of Bayesian networks is due to their capability to simply represent (in)dependence and to be a compact representation of a full joint distribution of the set of random variables involved in the studied system. Since belief function theory is known as a general framework to reason under uncertainty, it is expected that belief function ...
Imen Boukhris, Zied Elouedi, Salem Benferhat   +2 more
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Functional belief and judgmental belief

Synthese, 2017
A division between functional (animal) belief, on the one hand, and judgmental (reflective) belief, on the other, is central to Sosa’s two-tier virtue epistemology. For Sosa, mere functional belief is constituted by a first-order affirmation (or, perhaps, a simple disposition to affirm). In contrast, a judgmental belief is an intentional affirmation; a
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APPROXIMATION OF BELIEF FUNCTIONS

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2003
This paper addresses the approximation of belief functions by probability functions where the approximation is based on minimizing the Euclidean distance. First of all, we simplify this optimization problem so it becomes equivalent to a standard problem in linear algebra.
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On belief functions

1992
The present state of development of Dempster-Shafer theory is surveyed and its place among theories of dealing with uncertainty in AI is discussed. No knowledge of the theory is assumed.
Petr Hájek, David Harmanec
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ON THE POLYTOPES OF BELIEF AND PLAUSIBILITY FUNCTIONS

International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2010
In this paper we study some properties of the polytope of belief functions on a finite referential. These properties can be used in the problem of identification of a belief function from sample data. More concretely, we study the set of isometries, the set of invariant measures and the adjacency structure.
Pedro Miranda 0002, Elías F. Combarro
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