Measuring Consensus Effectiveness by a Generalized Entropy Criterion

Authors:
Harry E. Stephanou;Shin-Yee Lu
Affiliations:
George Mason Univ., Fairfax, VA;-
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1988

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Abstract

A quantitative criterion for measuring the effectiveness of the consensus obtained by pooling evidence from two knowledge sources is introduced. A brief review of the Dempster-Shafer theory of mathematical evidence, which is based on a set-theoretic description of subjective uncertainty, is given. The concept of generalized entropy as a measure of the uncertainty in a knowledge source is also introduced. It is proven that the pooling of evidence by Dempster's rule of combination decreases the total amount of generalized entropy in the knowledge sources. The decrease of entropy corresponds to the focusing of knowledge, and is used as a measure of consensus effectiveness. Several examples are used to illustrate this measure.