Updating Knowledge Bases with Disjunctive Information

No. 1: Agents, AI in Art and Entertainment, Knowledge Representation, and Learning

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 13

Knowledge Representation Belief & Belief Revision

It is well known that the minimal change principle was widely used in knowledge base updates. However, recent research has shown that conventional minimal change methods, eg. the PMA (Winslett 1988), are generally problematic for updating knowledge bases with disjunctive information. In this paper, we propose two different approaches to deal with this problem - one is called the minimal change with exceptions (MCE), the other is called the minimal change with maximal disjunctive inclusions (MCD). The first method is syntax-based, while the second is model-theoretic. We show that these two approaches are equivalent for propositional knowledge base updates, and the second method is also appropriate for first order knowledge base updates. We then prove that our new update approaches still satisfy the standard Katsuno and Mendelzon’s update postulates.