Advantages and a Limitation of Using LEG Nets in a Real-TIme Problem
  After experimenting with a number of non-probabilistic methods for dealing
with uncertainty many researchers reaffirm a preference for probability methods
[1] [2], although this remains controversial. The importance of being able to
form decisions from incomplete data in diagnostic problems has highlighted
probabilistic methods [5] which compute posterior probabilities from prior
distributions in a way similar to Bayes Rule, and thus are called Bayesian
methods. This paper documents the use of a Bayesian method in a real time
problem which is similar to medical diagnosis in that there is a need to form
decisions and take some action without complete knowledge of conditions in the
problem domain. This particular method has a limitation which is discussed.
