Using Conditional Independence for Belief Revision

Authors: Matthew James Lynn, James P. Delgrande, Pavlos Peppas5809-5816

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Reproducibility Variable Result LLM Response
Research Type Theoretical We present an approach to incorporating qualitative assertions of conditional irrelevance into belief revision, in order to address the limitations of existing work which considers only unconditional irrelevance. We introduce two related notions of what it means for a multivalued dependency to be taken into account by a belief revision operator: partial and full compliance. We provide characterisations of partially and fully compliant belief revision operators in terms of semantic conditions on their associated faithful rankings. Using these characterisations, we show that the constraints for partially and fully compliant belief revision operators are compatible with the AGM postulates. Furthermore, we provide representation results, giving conditions on faithful rankings which correspond to the sets of postulates characterising conditional independence in revision.
Researcher Affiliation Academia Matthew James Lynn,1 James P. Delgrande,1 Pavlos Peppas2 1Simon Fraser University, Canada 2University of Patras, Greece mlynn@cs.sfu.ca, jim@cs.sfu.ca, pavlos@upatras.gr
Pseudocode No The paper contains formal definitions, theorems, and proofs but no pseudocode or algorithm blocks.
Open Source Code No The paper does not mention providing open-source code for the described methodology.
Open Datasets No The paper is theoretical and does not use or describe any datasets for training.
Dataset Splits No The paper is theoretical and does not involve dataset splits.
Hardware Specification No The paper describes theoretical work and does not mention any hardware specifications for experiments.
Software Dependencies No The paper is theoretical and does not mention specific software dependencies with version numbers.
Experiment Setup No The paper is theoretical and does not describe any experimental setup details or hyperparameters.