Upgrading Ambiguous Signs in QPNs
  WA qualitative probabilistic network models the probabilistic relationships
between its variables by means of signs. Non-monotonic influences have
associated an ambiguous sign. These ambiguous signs typically lead to
uninformative results upon inference. A non-monotonic influence can, however,
be associated with a, more informative, sign that indicates its effect in the
current state of the network. To capture this effect, we introduce the concept
of situational sign. Furthermore, if the network converts to a state in which
all variables that provoke the non-monotonicity have been observed, a
non-monotonic influence reduces to a monotonic influence. We study the
persistence and propagation of situational signs upon inference and give a
method to establish the sign of a reduced influence.
