Deriving minimal conflict sets by CS-trees with mark set in diagnosis from first principles

Abstract

To discriminate among all possible diagnoses using Hou's theory of measurement in diagnosis from first principles, one has to derive all minimal conflict sets from a known conflict set. However, the result derived from Hou's method depends on the order of node generation in CS-trees. We develop a derivation method with mark set to overcome this drawback of Hou's method. We also show that our method is more efficient in the sense that no redundant tests have to be done. An enhancement to our method with the aid of extra information is presented. Finally, a discussion on top-down and bottom-up derivations is given.