Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
On the concept of possibility-probability consistency
Fuzzy Sets and Systems
The principle of minimum specificity as a basis for evidential reasoning
Processing and Management of Uncertainty in Knowledge-Based Systems on Uncertainty in knowledge-based systems. International Conference on Information
Fuzzy sets in approximate reasoning, part 1: inference with possibility distributions
Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
Fuzzy sets in approximate reasoning, part 2: logical approaches
Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
Default knowledge and measures of specificity
Information Sciences: an International Journal
Uncertainty-Based Information: Elements of Generalized Information Theory
Uncertainty-Based Information: Elements of Generalized Information Theory
Credibility discounting in the theory of approximate reasoning
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Precisiated natural language (PNL)
AI Magazine
Toward a generalized theory of uncertainty (GTU): an outline
Information Sciences—Informatics and Computer Science: An International Journal
Unfair coins and necessity measures: Towards a possibilistic interpretation of histograms
Fuzzy Sets and Systems
A notion of comparative probabilistic entropy based on the possibilistic specificity ordering
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On Possibilistic and Probabilistic Information Fusion
International Journal of Fuzzy System Applications
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Our main result here is the development of a general procedure for transforming some initial probability distribution into a new probability distribution in a way that the resulting distribution has entropy at least as great as the original distribution.A significant aspect of our approach is that it makes use of Zadeh's entailment principle which is itself a general procedure for going from an initial possibility distribution to a new possibility distribution so that the resulting possibility has an uncertainty at least as great as the original.