Language splitting and relevance-based belief change in Horn logic

Maonian Wu, Dongmo Zhang, Mingyi Zhang

    Research output: Chapter in Book / Conference PaperConference Paperpeer-review

    Abstract

    ![CDATA[This paper presents a framework for relevance-based belief change in propositional Horn logic.We firstly establish a parallel interpolation theorem for Horn logic and show that Parikh’s Finest Splitting Theorem holds with Horn formulae. By reformulating Parikh’s relevance criterion in the setting of Horn belief change, we construct a relevance-based partial meet Horn contraction operator and provide a representation theorem for the operator. Interestingly, we find that this contraction operator can be fully characterised by Delgrande and Wassermann’s postulates for partial meet Horn contraction as well as Parikh’s relevance postulate without requiring any change on the postulates, which is qualitatively different from the case in classical propositional logic.]]
    Original languageEnglish
    Title of host publicationProceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence and the Twentry-Third Innovative Applications of Artificial Intelligence: 7-11 August 2011, San Francisco, California, USA
    PublisherAAAI Press
    Pages268-273
    Number of pages6
    ISBN (Print)9781577355083
    Publication statusPublished - 2011
    EventAAAI Conference on Artificial Intelligence -
    Duration: 22 Jul 2012 → …

    Conference

    ConferenceAAAI Conference on Artificial Intelligence
    Period22/07/12 → …

    Fingerprint

    Dive into the research topics of 'Language splitting and relevance-based belief change in Horn logic'. Together they form a unique fingerprint.

    Cite this