Combining databases with prioritized information

To solve a problem one may need to combine the knowledge of several different experts. It can happen that some of the claims of one or more experts may be in conflict with the claims of other experts. There may be several such points of conflict and any claim may be involved in several different such points of conflict. In that case, the user of the knowledge of experts may prefer a certain claim to another in one conflict-point without necessarily preferring that statement in another conflict-point. Our work constructs a framework within which the consequences of a set of such preferences (expressed as priorities among sets of statements) can be computed. We give four types of semantics for priorities, three of which are shown to be equivalent to one another. The fourth type of semantics for priorities is shown to be more cautious than the other three. In terms of these semantics for priorities, we give a function for combining knowledge from different sources such that the combined knowledge is conflict-free and satisfies all the priorities.