Modeling belief in dynamic systems - Part II: Revision and update

The study of belief change has been an active area in philosophy and AI. In recent years two special cases of belief change, belief revision and belie f update, have been studied in detail. In a companion paper (Friedman & Hal pern, 1997), we introduce a new framework to model belief change. This fram ework combines temporal and epistemic modalities with a notion of plausibil ity, allowing us to examine the change of beliefs over time. In this paper, we show how belief revision and belief update can be captured in our frame work. This allows us to compare the assumptions made by each method, and to better understand the principles underlying them. In particular, it shows that Katsuno and Mendelzon's notion of belief update (Katsuno & Mendelzon, 1991a) depends on several strong assumptions that may limit its applicabili ty in artificial intelligence. Finally, our analysis allow us to identify a notion of minimal change that underlies a broad range of belief change ope rations including revision and update.