Generalized Update: Belief Change in Dynamic Settings

Craig Boutilier
Department of Computer Science
University of British Columbia
Vancouver, BC, CANADA, V6T 1Z4

Belief revision and belief update have been proposed as two types of belief change serving different purposes. Belief revision, as exemplified by the classic AGM theory, is intended to capture changes of an agent's belief state reflecting new information about a static world. Belief update, as specified by Katsuno and Mendelzon, is intended to capture changes of belief in response to a changing world. We argue that both belief revision and belief update are too restrictive; routine belief change involves elements of both. We present a model for generalized update that allows updates in response to external changes to inform the agent about its prior beliefs. This model of update combines aspects of revision and update, providing a more realistic characterization of belief change. We show that, under certain assumptions, the original update postulates are satisfied. We also demonstrate the plain revision and plain update are special cases of our model, in a way that formally verifies the intuition that revision is suitable for ``static'' belief change.

Appeared IJCAI-95

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