Classic Works of the Dempster-Shafer Theory of Belief Functions

By: Ronald R. Yager (Editor), Liping Liu (Editor)

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Hardcover | 22 February 2008

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828 Pages

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23.39 x 15.6 x 4.45

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This book brings together a collection of classic research papers on the Dempster-Shafer theory of belief functions. This book will serve as the authoritative reference in the field of evidential reasoning and an important archival reference in a wide range of areas including uncertainty reasoning in artificial intelligence and decision making in economics, engineering, and management. The carefully selected contributions are grouped into seven sections, including conceptual foundations, theoretical perspectives, theoretical extensions, alternative interpretations, and applications to artificial intelligence, decision-making, and statistical inferences. The book also includes a foreword by Dempster and Shafer reflecting the development of the theory in the last forty years, and an introduction describing the basic elements of the theory and how each paper contributes to the field.

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Classic works of the Dempster-Shafer theory of belief functions : an introduction	p. 1
New methods for reasoning towards posterior distributions based on sample data	p. 35
Upper and lower probabilities induced by a multivalued mapping	p. 57
A generalization of Bayesian inference	p. 73
On random sets and belief functions	p. 105
Non-additive probabilities in the work of Bernoulli and Lambert	p. 117
Allocations of probability	p. 183
Computational methods for a mathematical theory of evidence	p. 197
Constructive probability	p. 217
Belief functions and parametric models	p. 265
Entropy and specificity in a mathematical theory of evidence	p. 291
A method for managing evidential reasoning in a hierarchical hypothesis space	p. 311
Languages and designs for probability judgment	p. 345
A set-theoretic view of belief functions	p. 375
Weights of evidence and internal conflict for support functions	p. 411
A framework for evidential-reasoning systems	p. 419
Epistemic logics, probability, and the calculus of evidence	p. 435
Implementing Dempster's rule for hierarchical evidence	p. 449
Some characterizations of lower probabilities and other monotone capacities through the use of Mobius inversion	p. 477
Axioms for probability and belief-function propagation	p. 499
Generalizing the Dempster-Shafer theory to fuzzy sets	p. 529
Bayesian updating and belief functions	p. 555
Belief-function formulas for audit risk	p. 577
Decision making under Dempster-Shafer uncertainties	p. 619
Belief functions : the disjunctive rule of combination and the generalized Bayesian theorem	p. 633
Representation of evidence by hints	p. 665
Combining the results of several neural network classifiers	p. 683
The transferable belief model	p. 693
A k-nearest neighbor classification rule based on Dempster-Shafer theory	p. 737
Logicist statistics II : inference	p. 761
About editors	p. 787
About authors	p. 789
Author index	p. 799
Subject index	p. 801
Table of Contents provided by Blackwell. All Rights Reserved.

Classic Works of the Dempster-Shafer Theory of Belief Functions

At a Glance

Hardcover

Shipping

How to return your order

Defective items

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Other Editions and Formats

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