1. A system for automatically determining a set of at least one maximal utility object from a set of at least one object represented by a probabilistic model, comprising: determining an upper bound for the utility of each object; sorting the objects by the upper bounds in order of highest to lowest; obtaining a set of known object values for a particular entity; using the probabilistic model in combination with the information known about an entity to begin predicting the set of maximal utility objects from the set of objects; examining the utilities associated with each object in the set of objects in the sorted order for selecting maximal utility objects until the set of maximal utility objects us full; and continuing the examination of utilities until the utility associated with a lowest utility object in the set of maximal utility objects is greater than the upper bound of the utility of a next sorted object in the set of objects.