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  • Extending AGM contraction to arbitrary logics

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    ZhuangPUB895.pdf (546.4Kb)
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    Author(s)
    Zhuang, Zhiqiang
    Wang, Zhe
    Wang, Kewen
    Delgrande, James P
    Griffith University Author(s)
    Wang, Kewen
    Wang, Zhe
    Zhuang, Zhiqiang
    Year published
    2015
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    Abstract
    Classic entrenchment-based contraction is not applicable to many useful logics, such as description logics. This is because the semantic construction refers to arbitrary disjunctions of formulas, while many logics do not fully support disjunction. In this paper, we present a new entrenchment-based contraction which does not rely on any logical connectives except conjunction. This contraction is applicable to all fragments of first-order logic that support conjunction. We provide a representation theorem for the contraction which shows that it satisfies all the AGM postulates except for the controversial Recovery Postulate, ...
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    Classic entrenchment-based contraction is not applicable to many useful logics, such as description logics. This is because the semantic construction refers to arbitrary disjunctions of formulas, while many logics do not fully support disjunction. In this paper, we present a new entrenchment-based contraction which does not rely on any logical connectives except conjunction. This contraction is applicable to all fragments of first-order logic that support conjunction. We provide a representation theorem for the contraction which shows that it satisfies all the AGM postulates except for the controversial Recovery Postulate, and is a natural generalisation of entrenchment-based contraction.
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    Journal Title
    Proceedings of the International Joint Conference on Artificial Intelligence
    Volume
    2015
    Publisher URI
    https://www.ijcai.org/Abstract/15/465
    Copyright Statement
    © 2015 International Joint Conference on Artificial Intelligence. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
    Subject
    Artificial Intelligence and Image Processing not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/125325
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    • Journal articles

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