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Article
Interval probability theory for evidential support
Article first published online: 13 MAR 2007
DOI: 10.1002/int.4550050204
Copyright © 1990 Wiley Periodicals, Inc., A Wiley Company
1098-111X/asset/cover.gif?v=1&s=7f7c12f2c86265974044b2b3f9936860ffc468a0 "International Journal of Intelligent Systems")
Additional Information
How to Cite
Cui, W. and Blockley, D. I. (1990), Interval probability theory for evidential support. International Journal of Intelligent Systems, 5: 183–192. doi: 10.1002/int.4550050204
Publication History
- Issue published online: 13 MAR 2007
- Article first published online: 13 MAR 2007
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Abstract
An interval theory of probability is presented for use as a measure of evidential support in knowledge-based systems. an interval number is used to capture, in a relatively simple manner, features of fuzziness and incompleteness. the vertex method is used for the interval analysis. A new parameter (also an interval number), p, called the degree of dependence is introduced. the relationship of this interval probability with the theories of Dempster-Shafer, fuzzy sets, and Baldwin's support logic are discussed. the advantage of the theory is that it is based on a development of the axioms of probability, but allows that evidential support for a conjecture be separated from evidential support for the negation of the conjecture.