Classic Works of the Dempster-Shafer Theory of Belief Functions
This book brings together a collection of classic research papers on the Dempster-Shafer theory of belief functions. By bridging fuzzy logic and probabilistic reasoning, the theory of belief functions has become a primary tool for knowledge representation and uncertainty reasoning in expert systems....
Bewaard in:
| Hoofdauteur: | |
|---|---|
| Andere auteurs: | |
| Formaat: | Livre numérique |
| Taal: | Anglais |
| Gepubliceerd in: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Editie: | 1st ed. 2008. |
| Reeks: | Studies in Fuzziness and Soft Computing
219 |
| Online toegang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Opmerking: |
Le nom Ronald R. Yager a été mal orthographié en Roland R. Yager. Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Classic works on the Dempster-Shafer theory of belief functions, Ronald Yager, Liping Liu (Eds.), Berlin, Springer, 2008, 1 vol. (XIX-806 p.), Studies in fuzziness and soft computing, 978-3-540-25381-5 |
Inhoudsopgave:
- 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