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A Constructive Approach to Independent and Evidence Retaining Belief Revision by General Information Sets

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Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 937-941.

https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-162

Abstract

Recent years have seen a lot of work towards extending the established AGM belief revision theory with respect to iterating revision, preserving conditional beliefs, and handling sets of propositions as new information. In particular, novel postulates like independence and evidence retainment have been brought forth as new standards for revising epistemic states by (sets of) propositional information. In this paper, we propose a constructive approach for revising epistemic states by sets of (propositional and conditional) beliefs that combines ideas from nonmonotonic reasoning with conditional belief revision. We also propose a novel principle called enforcement that covers both independence and evidence retainment, and we show our revision operator to comply with major postulates from the literature. Moreover, we point out the relevance of our approach for default reasoning.

Gabriele Kern-Isberner, and Patrick Krümpelmann. 2011. A Constructive Approach to Independent and Evidence Retaining Belief Revision by General Information Sets. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11. IJCAI, 937–941. https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-162
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