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Duration Consistency Filtering for Qualitative Simulation

dc.contributor.authorKönik, Tolgaen_US
dc.contributor.authorCem Say, A. C.en_US
dc.date.accessioned2006-09-08T19:37:20Z
dc.date.available2006-09-08T19:37:20Z
dc.date.issued2003-08en_US
dc.identifier.citationKönik, Tolga; Cem Say, A.C.; (2003). "Duration Consistency Filtering for Qualitative Simulation." Annals of Mathematics and Artificial Intelligence 38(4): 269-309. <http://hdl.handle.net/2027.42/41773>en_US
dc.identifier.issn1012-2443en_US
dc.identifier.issn1573-7470en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/41773
dc.description.abstractWe present two new qualitative reasoning formalisms, and use them in the construction of a new type of filtering mechanism for qualitative simulators. Our new sign algebra, SR1*, facilitates reasoning about relationships among the signs of collections of real numbers. The comparison calculus , built on top of SR1*, is a general framework that can be used to qualitatively compare the behaviors of two dynamic systems or two excerpts of the behavior of a single dynamic system at different situations. These tools enable us to improve the predictive performance of qualitative simulation algorithms. We show that qualitative simulators can make better use of their input to deduce significant amounts of qualitative information about the relative lengths of the time intervals in their output behavior predictions. Simple techniques employing concepts like symmetry, periodicity, and comparison of the circumstances during multiple traversals of the same region can be used to build a list of facts representing the deduced information about relative durations. The duration consistency filter eliminates spurious behaviors leading to inconsistent combinations of these facts. Surviving behaviors are annotated with richer qualitative descriptions. Used in conjunction with other spurious behavior elimination methods, this approach would increase the ability of qualitative simulators to handle more complex systems.en_US
dc.format.extent313475 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.subject.otherQualitative Reasoningen_US
dc.subject.otherQualitative Simulationen_US
dc.subject.otherSpurious Behavior Filteringen_US
dc.subject.otherSign Algebraen_US
dc.subject.otherQualitative Comparisonen_US
dc.titleDuration Consistency Filtering for Qualitative Simulationen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelScience (General)en_US
dc.subject.hlbsecondlevelComputer Scienceen_US
dc.subject.hlbtoplevelScienceen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumArtificial Intelligence Lab., University of Michigan, Advanced Tech. Bldg., 1101 Beal Ave., Ann Arbor, MI, 48109-2110, USAen_US
dc.contributor.affiliationotherDepartment of Computer Engineering, Boğaziçi University, Bebek, 34342, İstanbul, Turkeyen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/41773/1/10472_2004_Article_5118515.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1023/A:1023080709134en_US
dc.identifier.sourceAnnals of Mathematics and Artificial Intelligenceen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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