A New Approach to Knowledge Base Revision in DL-Lite
Revising knowledge bases (KBs) in description logics (DLs) in a syntax-independent manner is an important, nontrivial problem for the ontology management and DL communities. Several attempts have been made to adapt classical modelbased belief revision and update techniques to DLs, but they are restricted in several ways. In particular, they do not provide operators or algorithms for general DL KB revision. The key difficulty is that, unlike propositional logic, a DL KB may have infinitely many models with complex (and possibly infinite) structures, making it difficult to define and compute revisions in terms of models. In this paper, we study general KBs in a specific DL in the DL-Lite family. We introduce the concept of features for such KBs, develop an alternative semantic characterization of KBs using features (instead of models), define two specific revision operators for KBs, and present the first algorithm for computing best approximations for syntax-independent revisions of KBs.
Proceedings of the Twenty-fourth AAAI Conference on Artificial Intelligence and the Twenty-second Innovative Applications of Artificial Intelligence Conference, the First Symposium on Educational Advance (AAAI-10)
Numerical and Computational Mathematics not elsewhere classified