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Classic Works of the Dempster-Shafe
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- ISBN-13
- 9783642064784
- Book Title
- Classic Works of the Dempster-Shafer Theory of Belief Functions
- ISBN
- 9783642064784
- Subject Area
- Mathematics, Computers, Technology & Engineering
- Publication Name
- Classic Works of the Dempster-Shafer Theory of Belief Functions
- Publisher
- Springer Berlin / Heidelberg
- Item Length
- 9.3 in
- Subject
- Engineering (General), Intelligence (Ai) & Semantics, Applied
- Publication Year
- 2010
- Series
- Studies in Fuzziness and Soft Computing Ser.
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Item Weight
- 44 Oz
- Item Width
- 6.1 in
- Number of Pages
- Xix, 806 Pages
關於產品
Product Identifiers
Publisher
Springer Berlin / Heidelberg
ISBN-10
3642064787
ISBN-13
9783642064784
eBay Product ID (ePID)
109047949
Product Key Features
Number of Pages
Xix, 806 Pages
Language
English
Publication Name
Classic Works of the Dempster-Shafer Theory of Belief Functions
Publication Year
2010
Subject
Engineering (General), Intelligence (Ai) & Semantics, Applied
Type
Textbook
Subject Area
Mathematics, Computers, Technology & Engineering
Series
Studies in Fuzziness and Soft Computing Ser.
Format
Trade Paperback
Dimensions
Item Weight
44 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Intended Audience
Scholarly & Professional
Series Volume Number
219
Number of Volumes
1 vol.
Illustrated
Yes
Table Of Content
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.
Synopsis
This volume is a welcome addition to the literature on the Dempster-Shafer theory. It mayhelp turn the theory, which now enjoys a lively but fragmented existence, into a more coherent and better understood set of tools for pro- bilistic thinking in science and technology. Thevolume'stitlesuggeststhatthetheoryhadaclassicalperiodextending from the 1960s through the 1980s. In its ?rst two decades, it consisted of theoretical writings by the two of us: Dempster's work on upper and lower probabilities in the 1960s and Shafer's work on belief functions in the 1970s. Then interestinapplications suddenly ?owered.After Je?Barnettintroduced thename"Dempster-Shafer"in1981[1],thetheoryquicklyacquiredtextbook statusinarti'cialintelligence.Bytheendoftheclassicalperiod,around1990, the theory had acquired powerful computational tools, remarkably diverse applications, and the attention of many researchers interested in variations and generalizations. By many measures, the theory continues to ?ourish in the 21st century. Internet searches for "Dempster-Shafer" produce ever more hits. The theory is used in many branches of technology,only a few of which are representedin thisvolume.Articlesonthetheoryanditsapplicationsappearinaremarkable number of journals and recurring conferences. Books on the theory continue to appear. In other important respects, however, the theory has not been moving forward.Westillhearquestionsthatwereaskedinthe1980s:Howdowetellif bodiesofevidenceareindependent?Whatdowedoiftheyaredependent?We still encounter confusion and disagreement about how to interpret the theory. And we still ?nd little acceptance of the theory in mathematical statistics, where it ?rst began 40 years ago. We have come to believe that three things are needed to move the theory forward., 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.
LC Classification Number
TA329-348
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