Classic Works of the Dempster-Shafer Theory of Belief Functions / Edition 1

Classic Works of the Dempster-Shafer Theory of Belief Functions / Edition 1

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by Ronald R. Yager
     
 

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ISBN-10: 3642064787

ISBN-13: 9783642064784

Pub. Date: 11/23/2010

Publisher: Springer Berlin Heidelberg

This is a collection of classic research papers on the Dempster-Shafer theory of belief functions. The book is 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 book

Overview

This is a collection of classic research papers on the Dempster-Shafer theory of belief functions. The book is 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 book includes a foreword reflecting the development of the theory in the last forty years.

Product Details

ISBN-13:
9783642064784
Publisher:
Springer Berlin Heidelberg
Publication date:
11/23/2010
Series:
Studies in Fuzziness and Soft Computing Series , #219
Edition description:
Softcover reprint of hardcover 1st ed. 2008
Pages:
806
Product dimensions:
6.10(w) x 9.25(h) x 0.06(d)

Table of Contents

Classic Works of the Dempster-Shafer Theory of Belief Functions: An Introduction.- New Methods for Reasoning Towards Posterior Distributions Based on Sample Data.- Upper and Lower Probabilities Induced by a Multivalued Mapping.- A Generalization of Bayesian Inference.- On Random Sets and Belief Functions.- Non-Additive Probabilities in the Work of Bernoulli and Lambert.- Allocations of Probability.- Computational Methods for A Mathematical Theory of Evidence.- Constructive Probability.- Belief Functions and Parametric Models.- Entropy and Specificity in a Mathematical Theory of Evidence.- A Method for Managing Evidential Reasoning in a Hierarchical Hypothesis Space.- Languages and Designs for Probability Judgment.- A Set-Theoretic View of Belief Functions.- Weights of Evidence and Internal Conflict for Support Functions.- A Framework for Evidential-Reasoning Systems.- Epistemic Logics, Probability, and the Calculus of Evidence.- Implementing Dempster’s Rule for Hierarchical Evidence.- Some Characterizations of Lower Probabilities and Other Monotone Capacities through the use of Möbius Inversion.- Axioms for Probability and Belief-Function Propagation.- Generalizing the Dempster–Shafer Theory to Fuzzy Sets.- Bayesian Updating and Belief Functions.- Belief-Function Formulas for Audit Risk.- Decision Making Under Dempster–Shafer Uncertainties.- Belief Functions: The Disjunctive Rule of Combination and the Generalized Bayesian Theorem.- Representation of Evidence by Hints.- Combining the Results of Several Neural Network Classifiers.- The Transferable Belief Model.- A k-Nearest Neighbor Classification Rule Based on Dempster-Shafer Theory.- Logicist Statistics II: Inference.

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Classic Works of the Dempster-Shafer Theory of Belief Functions 5 out of 5 based on 0 ratings. 1 reviews.
Anonymous More than 1 year ago
We used the book for a research seminar at Harvard. My professor highly regards the book and considers it the bible on the Dempster-Shafer theory of belief functions.