Artificial Intelligence


Analyzing the Monotonicity of Belief Interval Based Uncertainty Measures in Belief Function Theory

Authors: Xinyang Deng, Shiyu Wang, Yong Deng

Measuring the uncertainty of pieces of evidence is an open issue in belief function theory. A rational uncertainty measure for belief functions should meet some desirable properties, where monotonicity is an very important property. Recently, measuring the total uncertainty of a belief function based on its associated belief intervals becomes a new research idea and have attracted increasing interest. Several belief interval based uncertainty measures have been proposed for belief functions. In this paper, we summarize the properties of these uncertainty measures and especially investigate whether the monotonicity is satisfied by the measures. This study provide a comprehensive comparison to these belief interval based uncertainty measures and is very useful for choosing the appropriate uncertainty measure in the practical applications.

Comments: 21 Pages.

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Submission history

[v1] 2017-09-06 07:32:22

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