  Reasoning under uncertainty in Al hats come to mean assessing the credibility
of hypotheses inferred from evidence. But techniques for assessing credibility
do not tell a problem solver what to do when it is uncertain. This is the focus
of our current research. We have developed a medical expert system called MUM,
for Managing Uncertainty in Medicine, that plans diagnostic sequences of
questions, tests, and treatments. This paper describes the kinds of problems
that MUM was designed to solve and gives a brief description of its
architecture. More recently, we have built an empty version of MUM called MU,
and used it to reimplement MUM and a small diagnostic system for plant
pathology. The latter part of the paper describes the features of MU that make
it appropriate for building expert systems that manage uncertainty.
