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A Syntactic Approach to Revising Epistemic States with Uncertain Inputs

  • Kim Bauters
  • , Weiru Liu
  • , Jun Hong
  • , Lluis Godo
  • , Carles Sierra

    Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

    2 Citations (Scopus)
    312 Downloads (Pure)

    Abstract

    Revising its beliefs when receiving new information is an important ability of any intelligent system. However, in realistic settings the new input is not always certain. A compelling way of dealing with uncertain input in an agent-based setting is to treat it as unreliable input, which may strengthen or weaken the beliefs of the agent. Recent work focused on the postulates associated with this form of belief change and on finding semantical operators that satisfy these postulates. In this paper we propose a new syntactic approach for this form of belief change and show that it agrees with the semantical definition. This makes it feasible to develop complex agent systems capable of efficiently dealing with unreliable input in a semantically meaningful way. Additionally, we show that imposing restrictions on the input and the beliefs that are entailed allows us to devise a tractable approach suitable for resource-bounded agents or agents where reactive ness is of paramount importance
    Original languageEnglish
    Title of host publication2014 IEEE 26th International Conference on Tools with Artificial Intelligence (ICTAI 2014)
    Subtitle of host publicationProceedings of a meeting held 10-12 November 2014, Limassol, Cyprus
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    Pages154-161
    Number of pages8
    ISBN (Electronic)9781479965724
    ISBN (Print)9781479965731
    DOIs
    Publication statusPublished - Feb 2015

    Publication series

    NameProceedings of the International Conference on Tools with Artificial Intelligence (ICTAI)
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    ISSN (Print)1082-3409

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