  In this paper, we develop a qualitative theory of influence diagrams that can
be used to model and solve sequential decision making tasks when only
qualitative (or imprecise) information is available. Our approach is based on
an order-of-magnitude approximation of both probabilities and utilities and
allows for specifying partially ordered preferences via sets of utility values.
We also propose a dedicated variable elimination algorithm that can be applied
for solving order-of-magnitude influence diagrams.
