A method for finding independently distributed probability models that satisfy order constraints

This research investigates a method that attempts to represent a database of expert decisions as an independent probability distribution. To implement this representation, our method searches for a simple probability model that exhibits maximum independence property and preserves a given set of inequality constraints. We show that finding such a representation can be formulated as a search problem over a log probability space with a representational complexity in a linear order of the number of variables. We show that the search can be achieved by employing linear programming technique in combination with a greedy (best first) search algorithm.