Wilhelm Rödder
FernUniversität Gesamthochschule in Hagen
Fachbereich Wirschaftswissenschaft, Lehrstuhl für Betriebswirtschaftslehre, insb. Operations Research
58084 Hagen
Germany
E-Mail: wilhelm.roedder@fernuni-hagen.de
Phone: ++49-2331-987-2635
Fax: ++49-2331-987-335
Longgui Xu
FernUniversität Gesamthochschule in Hagen
Fachbereich Wirschaftswissenschaft, Lehrstuhl für Betriebswirtschaftslehre, insb. Operations Research
58084 Hagen
Germany
E-Mail: longgui.xu@fernuni-hagen.de
Phone: ++49-2331-987-4107
Fax: ++49-2331-987-335
Probability distributions on a set of discrete variables are a suitable means to represent knowledge about their respective mutual dependencies. When now things become evident such a distribution can be adapted to the new situation and hence submitted to a sound inference process. Knowledge acquisition and inference are here performed in the rich syntax of conditional events. Both, acquisition and inference respect a sophisticated principle, namely that of maximum entropy and of minimum relative entropy. The freedom to formulate and derive knowledge in a language of rich syntax is comfortable but involves the danger of contradictions or inconsistencies. We develop a method how to solve such inconsistencies which go back to the incompatibility of experts’ knowledge in their respective branches. The method is applied to the diagnosis in Chinese medicine. All calculations are performed in the Entropy-driven expert system shell SPIRIT.
inference, entropy, inconsistency, expert system, SPIRIT
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