Modeling Beliefs in Dynamic Systesm. Part II: Revision and Update
N. Friedman and J. Y. Halpern
Submitted for publication.
A preliminary version appeared in J. Doyle, E.
Sandwell, and P. Torasso, eds. Principles of Knowledge
Representation and Reasoning: Proc. Fourth International Conference
(KR'94). Morgan Kaufman, San Francisco, CA. 1994. 190-201.
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 belief update, have been studied in
detail. In a companion paper, we introduce a new
framework to model belief change. This framework combines temporal and
epistemic modalities with a notion of plausibility, 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 framework.
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 depends on several strong
assumptions that may limit its applicability in artificial
Finally, our analysis allow us to identify a notion of minimal
change that underlies a broad range of belief change operations
including revision and update.
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