Xueming Huang, Gordon I. McCalla, Eric Neufeld
Belief revision for an intelligent system is usually computationally expensive. Here we tackle this problem by using focus in belief revision: that is, revision occurs only in a subset of beliefs under attention (or in focus). Attention can be shifted within the belief base, thus allowing use and revision of other subsets of beliefs. This attention-shifting belief revision architecture shows promise to allow efficient and natural revision of belief bases.