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dc.contributor.advisorShen, Qiangen
dc.contributor.authorMiguel, Ianen
dc.date.accessioned2004-01-27T17:07:50Z
dc.date.available2004-01-27T17:07:50Z
dc.date.issued2001-07
dc.identifier.urihttp://hdl.handle.net/1842/326
dc.descriptionCentre for Intelligent Systems and their Applicationsen
dc.descriptionstudentship 97305803en
dc.description.abstractConstraints are a natural means of knowledage representation in many disparate fields. A constraint often takes the form of an equation or inequality, but in the most abstract senseis simply a logical relation among several variables expressing a set of admissable value combinations. The following are simple examples: the sum of two variables must equal 30; no two adjacent countries on the map may be coloured the same. It is this generality and simplicity of structure which underly the ubiquity of the constraint-based representation in Atificial Intelligence.en
dc.contributor.sponsorEngineering and Physical Sciences Research Council (EPSRC)en
dc.format.extent3006855 bytesen
dc.format.mimetypeapplication/pdfen
dc.language.isoen
dc.publisherUniversity of Edinburgh. College of Science and Engineering. School of Informatics.en
dc.titleDynamic Flexible Constraint Satisfaction and it's Application to AI Planningen
dc.typeThesis or Dissertationen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD Doctor of Philosophyen


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