Constraint Propagation with Imprecise Conditional Probabilities
  An approach to reasoning with default rules where the proportion of
exceptions, or more generally the probability of encountering an exception, can
be at least roughly assessed is presented. It is based on local uncertainty
propagation rules which provide the best bracketing of a conditional
probability of interest from the knowledge of the bracketing of some other
conditional probabilities. A procedure that uses two such propagation rules
repeatedly is proposed in order to estimate any simple conditional probability
of interest from the available knowledge. The iterative procedure, that does
not require independence assumptions, looks promising with respect to the
linear programming method. Improved bounds for conditional probabilities are
given when independence assumptions hold.
