  In a probability-based reasoning system, Bayes' theorem and its variations
are often used to revise the system's beliefs. However, if the explicit
conditions and the implicit conditions of probability assignments `me properly
distinguished, it follows that Bayes' theorem is not a generally applicable
revision rule. Upon properly distinguishing belief revision from belief
updating, we see that Jeffrey's rule and its variations are not revision rules,
either. Without these distinctions, the limitation of the Bayesian approach is
often ignored or underestimated. Revision, in its general form, cannot be done
in the Bayesian approach, because a probability distribution function alone
does not contain the information needed by the operation.
