The Topological Fusion of Bayes Nets
  Bayes nets are relatively recent innovations. As a result, most of their
theoretical development has focused on the simplest class of single-author
models. The introduction of more sophisticated multiple-author settings raises
a variety of interesting questions. One such question involves the nature of
compromise and consensus. Posterior compromises let each model process all data
to arrive at an independent response, and then split the difference. Prior
compromises, on the other hand, force compromise to be reached on all points
before data is observed. This paper introduces prior compromises in a Bayes net
setting. It outlines the problem and develops an efficient algorithm for fusing
two directed acyclic graphs into a single, consensus structure, which may then
be used as the basis of a prior compromise.
