Consistency-based approaches to merging knowledge bases: preliminary report

We present a framework for investigating merging operators for belief sets. This framework is a generalisation of our earlier work concerning consistency-based belief revision and contraction. Two distinct merging operators are identified: in the first approach, belief sources are consistently combined so that the result of merging K1 and K2 is a maximal consistent (if possible) set of formulas comprising the joint knowledge of K1 and K2. This approach then accords to one’s intuitions as to what a “merge” operator should do. The second approach is more akin to a generalised belief revision operator: Two knowledge sources are “projected” onto a third (in the simplest case the trivially true knowledge base). In both cases, we consider the incorporation of entailment-based and consistency-based integrity constraints. Properties of these operators are investigated, primarily by comparing their properties with postulates that have been identified previously in the literature. As well, interrelationships between these approaches and belief revision are given.