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

14 Citations (Scopus)

Abstract

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 → …

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