Belief structures, possibility theory and decomposable confidence measures on finite sets
Computers and Artificial Intelligence
From Conditional Events to Conditional Measures: A New Axiomatic Approach
Annals of Mathematics and Artificial Intelligence
Independence and Possibilistic Conditioning
Annals of Mathematics and Artificial Intelligence
A theoretical framework for possibilistic independence in a weakly ordered setting
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Conditional possibility and necessity
Technologies for constructing intelligent systems
Comparative models ruled by possibility and necessity: A conditional world
International Journal of Approximate Reasoning
A view on conditional measures through local representability of binary relations
International Journal of Approximate Reasoning
An Axiomatization of Conditional Possibilistic Preference Functionals
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
T-conditional possibilities: Coherence and inference
Fuzzy Sets and Systems
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Any dynamic decision model or procedure for acquisition of knowledge must deal with conditional events and should refer to (not necessarily structured) domains containing only the elements and the information of interest. We consider conditional possibility theory as numerical reference model to handle uncertainty and to study binary relations, defined on an arbitrary set of conditional events expressing the idea of “no more possible than”. We give the necessary conditions for the representability of a relation by a T-conditional possibility, for any triangular norm T, and we provide a complete characterization in terms of necessary and sufficient conditions for the representability by a conditional possibility (i.e. when T is the minimum).