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  1. On the logic of iterated belief revision.Adnan Darwiche & Judea Pearl - 1997 - Artificial Intelligence 89 (1-2):1-29.
    We show in this paper that the AGM postulates are too weak to ensure the rational preservation of conditional beliefs during belief revision, thus permitting improper responses to sequences of observations. We remedy this weakness by proposing four additional postulates, which are sound relative to a qualitative version of probabilistic conditioning. Contrary to the AGM framework, the proposed postulates characterize belief revision as a process which may depend on elements of an epistemic state that are not necessarily captured by a (...)
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  • (1 other version)Ordinal Conditional Functions. A Dynamic Theory of Epistemic States.Wolfgang Spohn - 1988 - In W. L. Harper & B. Skyrms (eds.), Causation in Decision, Belief Change, and Statistics, vol. II. Kluwer Academic Publishers.
    It is natural and important to have a formal representation of plain belief, according to which propositions are held true, or held false, or neither. (In the paper this is called a deterministic representation of epistemic states). And it is of great philosophical importance to have a dynamic account of plain belief. AGM belief revision theory seems to provide such an account, but it founders at the problem of iterated belief revision, since it can generally account only for one step (...)
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  • Knowledge in Flux.Henry E. Kyburg & Peter Gardenfors - 1993 - Noûs 27 (4):519-521.
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  • Screened Revision.David Makinson - 1997 - Theoria 63 (1-2):14-23.
    Develops a concept of revision, akin in spirit to AGM partial meet revision, but in which the postulate of 'success' may fail. The basic idea is to see such an operation as composite, with a pre-processor using a priori considerations to resolve the question of whether to revise, following which another operation revises in a manner that protects the a priori material.
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  • (1 other version)On the logic of theory change: Partial meet contraction and revision functions.Carlos E. Alchourrón, Peter Gärdenfors & David Makinson - 1985 - Journal of Symbolic Logic 50 (2):510-530.
    This paper extends earlier work by its authors on formal aspects of the processes of contracting a theory to eliminate a proposition and revising a theory to introduce a proposition. In the course of the earlier work, Gardenfors developed general postulates of a more or less equational nature for such processes, whilst Alchourron and Makinson studied the particular case of contraction functions that are maximal, in the sense of yielding a maximal subset of the theory (or alternatively, of one of (...)
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  • Knowledge in Flux. Modelling the Dymanics of Epistemic States.P. Gärdenfors - 1988 - MIT Press.
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  • Semi-revision.Sven Hansson - 1997 - Journal of Applied Non-Classical Logics 7 (1-2):151-175.
    ABSTRACT Semi-revision is a mode of belief change that differs from revision in that the input sentence is not always accepted. A constructive approach to semi-revision is proposed. It requires an efficient treatment of local inconsistencies, which is more easily obtainable in belief base models than in belief set models. Axiomatic characterizations of two semi-revision operators are reported.
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  • Iterated revision and minimal change of conditional beliefs.Craig Boutilier - 1996 - Journal of Philosophical Logic 25 (3):263 - 305.
    We describe a model of iterated belief revision that extends the AGM theory of revision to account for the effect of a revision on the conditional beliefs of an agent. In particular, this model ensures that an agent makes as few changes as possible to the conditional component of its belief set. Adopting the Ramsey test, minimal conditional revision provides acceptance conditions for arbitrary right-nested conditionals. We show that problem of determining acceptance of any such nested conditional can be reduced (...)
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  • Propositional knowledge base revision and minimal change.Hirofumi Katsuno & Alberto O. Mendelzon - 1991 - Artificial Intelligence 52 (3):263-294.
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  • (1 other version)What does a conditional knowledge base entail?Daniel Lehmann & Menachem Magidor - 1992 - Artificial Intelligence 55 (1):1-60.
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  • Selective revision.Eduardo L. Fermé & Sven Ove Hansson - 1999 - Studia Logica 63 (3):331-342.
    We introduce a constructive model of selective belief revision in which it is possible to accept only a part of the input information. A selective revision operator ο is defined by the equality K ο α = K * f(α), where * is an AGM revision operator and f a function, typically with the property ⊢ α → f(α). Axiomatic characterizations are provided for three variants of selective revision.
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  • Non-prioritized belief revision based on distances between models.Karl Schlechta - 1997 - Theoria 63 (1-2):34-53.
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