  Bayes belief networks and influence diagrams are tools for constructing
coherent probabilistic representations of uncertain knowledge. The process of
constructing such a network to represent an expert's knowledge is used to
illustrate a variety of techniques which can facilitate the process of
structuring and quantifying uncertain relationships. These include some
generalizations of the "noisy OR gate" concept. Sensitivity analysis of generic
elements of Bayes' networks provides insight into when rough probability
assessments are sufficient and when greater precision may be important.
