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dc.contributor.authorSu, Kaileen_US
dc.contributor.authorSattar, Abdulen_US
dc.contributor.authorLv, Guanfengen_US
dc.contributor.authorZhang, Yanen_US
dc.date.accessioned2017-05-03T13:50:08Z
dc.date.available2017-05-03T13:50:08Z
dc.date.issued2009en_US
dc.date.modified2010-08-25T07:03:00Z
dc.identifier.issn10769757en_US
dc.identifier.doi10.1613/jair.2750en_AU
dc.identifier.urihttp://hdl.handle.net/10072/30908
dc.description.abstractIn this paper, we investigate knowledge reasoning within a simple framework called knowledge structure. We use variable forgetting as a basic operation for one agent to reason about its own or other agents/' knowledge. In our framework, two notions namely agents/' observable variables and the weakest sufficient condition play important roles in knowledge reasoning. Given a background knowledge base and a set of observable variables for each agent, we show that the notion of an agent knowing a formula can be defined as a weakest sufficient condition of the formula under background knowledge base. Moreover, we show how to capture the notion of common knowledge by using a generalized notion of weakest sufficient condition. Also, we show that public announcement operator can be conveniently dealt with via our notion of knowledge structure. Further, we explore the computational complexity of the problem whether an epistemic formula is realized in a knowledge structure. In the general case, this problem is PSPACE-hard; however, for some interesting subcases, it can be reduced to co-NP. Finally, we discuss possible applications of our framework in some interesting domains such as the automated analysis of the well-known muddy children puzzle and the verification of the revised Needham-Schroeder protocol. We believe that there are many scenarios where the natural presentation of the available information about knowledge is under the form of a knowledge structure. What makes it valuable compared with the corresponding multi-agent S5 Kripke structure is that it can be much more succinct.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent331344 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherA I Access Foundation, Incen_US
dc.publisher.placeUnited Statesen_US
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofpagefrom677en_US
dc.relation.ispartofpageto716en_US
dc.relation.ispartofjournalThe Journal of Artificial Intelligence Researchen_US
dc.relation.ispartofvolume35en_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchArtificial Intelligence and Image Processing not elsewhere classifieden_US
dc.subject.fieldofresearchcode080199en_US
dc.titleVariable Forgetting in Reasoning about Knowledgeen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.rights.copyrightCopyright 2009. A I Access Foundation, Inc. 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.en_AU
gro.date.issued2009
gro.hasfulltextFull Text


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