Abstract: 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. Key words and phrases
:
automated reasoning
, decision modeling
, probabilistic networks
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