Exact Reasoning Under Uncertainty
  This paper focuses on designing expert systems to support decision making in
complex, uncertain environments. In this context, our research indicates that
strictly probabilistic representations, which enable the use of
decision-theoretic reasoning, are highly preferable to recently proposed
alternatives (e.g., fuzzy set theory and Dempster-Shafer theory). Furthermore,
we discuss the language of influence diagrams and a corresponding methodology
-decision analysis -- that allows decision theory to be used effectively and
efficiently as a decision-making aid. Finally, we use RACHEL, a system that
helps infertile couples select medical treatments, to illustrate the
methodology of decision analysis as basis for expert decision systems.
