Interval structure: a framework for representing uncertain information

Authors:
S. K. M. Wong;L. S. Wang;Y. Y. Yao
Affiliations:
Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada;Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada;Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada
Venue:
UAI'92 Proceedings of the Eighth international conference on Uncertainty in artificial intelligence
Year:
1992

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Abstract

In this paper, a unified framework for representing uncertain information based on the notion of an interval structure is proposed. It is shown that the lower and upper approximations of the rough-set model, the lower and upper bounds of incidence calculus, and the belief and plausibility functions all obey the axioms of an interval structure. An interval structure can be used to synthesize the decision rules provided by the experts. An efficient algorithm to find the desirable set of rules is developed from a set of sound and complete inference axioms.