MAXIMUM ENTROPY ALGORITHMS FOR UNCERTAINTY MEASURES
- 1 September 1993
- journal article
- Published by World Scientific Pub Co Pte Ltd in International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
- Vol. 1 (1) , 69-93
- https://doi.org/10.1142/s021848859300005x
Abstract
In decision-making problems when probabilistic information is incomplete (e.g. Nguyen and Walker [1]) as well as in measuring the non-specificity and conflict in the theory of evidence (e.g. Maeda and Ichihashi [2, 3]), one is led to consider the problem of maximizing probabilistic entropy under a functional constraint induced by the available evidence. This paper is devoted specifically to developing computational algorithms for this optimization problem.Keywords
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