SPECIALIZATION—A NEW CONCEPT FOR UNCERTAINTY HANDLING WITH BELIEF FUNCTIONS
- 1 November 1990
- journal article
- research article
- Published by Taylor & Francis in International Journal of General Systems
- Vol. 18 (1) , 49-60
- https://doi.org/10.1080/03081079008935126
Abstract
Whenever methods for the treatment of uncertainty based on the theory of belief functions are presented in the literature they mostly rely on Dempster's rule of combination. The concept of specialization generalizes this rule and is less restrictive. It is founded on the fact that modelling uncertain phenomena always entails a simplifying coarsening which arises from the renounciation of a description to that depth a perfect image would require.Keywords
This publication has 7 references indexed in Scilit:
- Implementing Dempster's rule for hierarchical evidenceArtificial Intelligence, 1987
- Propagating belief functions in qualitative Markov treesInternational Journal of Approximate Reasoning, 1987
- The entailment principle for dempster—shafer granulesInternational Journal of Intelligent Systems, 1986
- A SET-THEORETIC VIEW OF BELIEF FUNCTIONS Logical operations and approximations by fuzzy sets†International Journal of General Systems, 1986
- A method for managing evidential reasoning in a hierarchical hypothesis spaceArtificial Intelligence, 1985
- A Mathematical Theory of EvidencePublished by Walter de Gruyter GmbH ,1976
- Upper and Lower Probabilities Induced by a Multivalued MappingThe Annals of Mathematical Statistics, 1967