Determining equivalent values for possibilistic variables.
We discuss the nature of possibilistic uncertainty. Two approaches to the determination of the equivalent value for a possibilistically uncertain variable are introduced. These approaches are then generalized to yield a parameterized class of functions for obtaining the equivalent value of a possibilistic variable. A novel aspect of this class is that it is parameterized by a weak ordering. A discussion to try to understand the semantics of this parameterizing ordering is included. A method is suggested for obtaining the weak ordering directly from a scalar value. We briefly look at the issue of variance in possibilistic uncertainty.
Yager
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Machine Intelligence Inst., New Rochelle, NY.