Incompletely Specified Probabilistic Networks

:Probabilistic networks, used as an adjunct or alternative to the logical models used in artificial intelligence (AI) and decision support systems (DSS), offer a way to compactly represent a distribution over a set of random variables. Nonetheless, the specification of a given network may require conditional probabilities that are simply unavailable. In this paper a means for analyzing incompletely specified networks is presented, and some general rules are derived from the application of the method to some simple networks. The use of the technique in MIS settings is illustrated.

• 저널Journal of Management Information Systems · 12(3) · 81–96
• 토픽Bayesian Modeling and Causal Inference · Artificial Intelligence
• DOI10.1080/07421222.1995.11518092
• 저자Stephen F. Roehrig