Notes on “Reducing Algorithm Complexity for Computing an Aggregate Uncertainty Measure”

In a recent paper, Liu have proposed the so-called F -algorithm which conditionally reduces the computational complexity of the Meyerowitz-Richman-Walker algorithm for the computation of the aggregate-uncertainty measure in the Dempster-Shafer theory of evidence, along with an illustration of its application in a practical scenario of target identification. In this correspondence, we will point out several technical mistakes, which some of them lead to some inexact or incomplete statements in the paper of Liu The corrections of these mistakes will be made, and some further improvement and results will be derived.