Iterated Belief Change
Aditya Ghose, Pablo Hadjinian, Abdul Rahman Sattar, Jia‐H. You, Randy G. Goebel · Computational Intelligence · 2004
Most existing formalizations treat belief change as a single‐step process, and ignore several problems that become important when a theory, or belief state, is revised over several steps. This paper identifies these problems, and argues for the need to retain all of the multiple possible outcomes of a belief change step, and for a framework in which the effects of a belief change step persist as long as is consistently possible. To demonstrate that such a formalization is indeed possible, we develop a framework, which uses the language of PJ‐default logic (Delgrande and Jackson 1991) to represent a belief state, and which enables the effects of a belief change step to persist by propagating belief constraints. Belief change in this framework maps one belief state to another, where each belief state is a collection of theories given by the set of extensions of the PJ‐default theory representing that belief state. Belief constraints do not need to be separately recorded; they are encoded as clearly identifiable components of a PJ‐default theory. The framework meets the requirements for iterated belief change that we identify and satisfies most of the AGM postulates (Alchourrón, Gärdenfors, and Makinson 1985) as well.