A Continuo Propagation Diagram Approach Reasoning nder Uncertainty
Qin Zhang · 1996
Reasoning under uncertainty is an important issue in artificial intelligent systems. A dynamic causality treeddiagram based method capable of dealing with complex cases like causality - loops has been presented in the companion paper [l]. But it, like most existing methods, considers only discrete cases and thus restricts its applications. Developed from it, this paper presents a new method to deal with continuous cases in which the ascendant, descendent and linkage variables can be continuous while keeping them independent of each other. The probability theory can not be rigorously applied but is somewhat relaxed. Therefore the uncertainty measure is called possibility instead of probability. An example is given to illustrate the method and show its new features.