On the Detection of Conflicts in Diagnostic Bayesian Networks Using
  Abstraction
  An important issue in the use of expert systems is the so-called brittleness
problem. Expert systems model only a limited part of the world. While the
explicit management of uncertainty in expert systems itigates the brittleness
problem, it is still possible for a system to be used, unwittingly, in ways
that the system is not prepared to address. Such a situation may be detected by
the method of straw models, first presented by Jensen et al. [1990] and later
generalized and justified by Laskey [1991]. We describe an algorithm, which we
have implemented, that takes as input an annotated diagnostic Bayesian network
(the base model) and constructs, without assistance, a bipartite network to be
used as a straw model. We show that in some cases this straw model is better
that the independent straw model of Jensen et al., the only other straw model
for which a construction algorithm has been designed and implemented.
