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Nonmonotonic consequences in default domain theory

dc.contributor.authorZhang, Guo‐qiangen_US
dc.contributor.authorRounds, William C.en_US
dc.date.accessioned2006-09-08T19:37:16Z
dc.date.available2006-09-08T19:37:16Z
dc.date.issued1997-03en_US
dc.identifier.citationZhang, Guo‐Qiang; Rounds, William C.; (1997). "Nonmonotonic consequences in default domain theory." Annals of Mathematics and Artificial Intelligence 20 (1-4): 227-265. <http://hdl.handle.net/2027.42/41772>en_US
dc.identifier.issn1012-2443en_US
dc.identifier.issn1573-7470en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/41772
dc.description.abstractDefault domain theory is a framework for representing and reasoning about commonsense knowledge. Although this theory is motivated by ideas in Reiter’s work on default logic, it is in some sense a dual framework. We make Reiter’s default extension operator into a constructive method of building models, not theories. Domain theory, which is a well established tool for representing partial information in the semantics of programming languages, is adopted as the basis for constructing partial models. This paper considers some of the laws of nonmonotonic consequence, due to Gabbay and to Kraus, Lehmann, and Magidor, in the light of default domain theory. We remark that in some cases Gabbay’s law of cautious monotony is open to question. We consider an axiomatization of the nonmonotonic consequence relation on prime open sets in the Scott topology – the natural logic – of a domain, which omits this law. We prove a representation theorem showing that such relations are in one to one correspondence with the consequence relations determined by extensions in Scott domains augmented with default sets. This means that defaults are very expressive: they can, in a sense, represent any reasonable nonmonotonic entailment. Results about what kind of defaults determine cautious monotony are also discussed. In particular, we show that the property of unique extensions guarantees cautious monotony, and we give several classes of default structures which determine unique extensions.en_US
dc.format.extent413834 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherKluwer Academic Publishers; Springer Science+Business Mediaen_US
dc.subject.otherComputer Scienceen_US
dc.subject.otherComputer Science, Generalen_US
dc.subject.otherArtificial Intelligence (Incl. Robotics)en_US
dc.subject.otherMathematics, Generalen_US
dc.subject.otherNonlinear Dynamics, Complex Systems, Chaos, Neural Networksen_US
dc.titleNonmonotonic consequences in default domain theoryen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelComputer Scienceen_US
dc.subject.hlbsecondlevelScience (General)en_US
dc.subject.hlbtoplevelScienceen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumArtificial Intelligence Laboratory, University of Michigan, Ann Arbor, Michigan, 48109, USAen_US
dc.contributor.affiliationotherDepartment of Computer Science, University of Georgia, Athens, Georgia, 30602, USAen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/41772/1/10472_2004_Article_325432.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1023/A:1018988629376en_US
dc.identifier.sourceAnnals of Mathematics and Artificial Intelligenceen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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