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Language Splitting and Relevance-Based Belief Change in Horn Logic

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

2 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 25th AAAI Conference on Artificial Intelligence, AAAI 2011
PublisherAAAI Press
Pages268-273
Number of pages6
ISBN (Electronic)9781577355083
Publication statusPublished - 11 Aug 2011
Event25th AAAI Conference on Artificial Intelligence, AAAI 2011 - San Francisco, United States
Duration: 7 Aug 201111 Aug 2011

Publication series

NameProceedings of the 25th AAAI Conference on Artificial Intelligence, AAAI 2011

Conference

Conference25th AAAI Conference on Artificial Intelligence, AAAI 2011
Country/TerritoryUnited States
CitySan Francisco
Period7/08/1111/08/11

Bibliographical note

Publisher Copyright:
Copyright © 2011, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

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