Defining Explanation in Probabilistic Systems
  As probabilistic systems gain popularity and are coming into wider use, the
need for a mechanism that explains the system's findings and recommendations
becomes more critical. The system will also need a mechanism for ordering
competing explanations. We examine two representative approaches to explanation
in the literature - one due to G\"ardenfors and one due to Pearl - and show
that both suffer from significant problems. We propose an approach to defining
a notion of "better explanation" that combines some of the features of both
together with more recent work by Pearl and others on causality.
