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Morphologic for knowledge dynamics: revision, fusion, abduction

Abstract : Several tasks in artificial intelligence require to be able to find models about knowledge dynamics. They include belief revision, fusion and belief merging, and abduction. In this paper we exploit the algebraic framework of mathematical morphology in the context of propositional logic, and define operations such as dilation or erosion of a set of formulas. We derive concrete operators, based on a semantic approach, that have an intuitive interpretation and that are formally well behaved, to perform revision, fusion and abduction. Computation and tractability are addressed, and simple examples illustrate the typical results that can be obtained.
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Submitted on : Friday, September 13, 2019 - 5:23:26 PM
Last modification on : Wednesday, November 3, 2021 - 6:17:50 AM


  • HAL Id : hal-02287815, version 1


Isabelle Bloch, Jérôme Lang, Ramon Pino Pérez, Carlos Uzcategui. Morphologic for knowledge dynamics: revision, fusion, abduction. [Research Report] arXiv:1802.05142v1, arXiv cs.AI. 2018. ⟨hal-02287815⟩



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