dc.contributor.advisor | Shen, Qiang | en |
dc.contributor.author | Miguel, Ian | en |
dc.date.accessioned | 2004-01-27T17:07:50Z | |
dc.date.available | 2004-01-27T17:07:50Z | |
dc.date.issued | 2001-07 | |
dc.identifier.uri | http://hdl.handle.net/1842/326 | |
dc.description | Centre for Intelligent Systems and their Applications | en |
dc.description | studentship 97305803 | en |
dc.description.abstract | Constraints 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.sponsor | Engineering and Physical Sciences Research Council (EPSRC) | en |
dc.format.extent | 3006855 bytes | en |
dc.format.mimetype | application/pdf | en |
dc.language.iso | en | |
dc.publisher | University of Edinburgh. College of Science and Engineering. School of Informatics. | en |
dc.title | Dynamic Flexible Constraint Satisfaction and it's Application to AI Planning | en |
dc.type | Thesis or Dissertation | en |
dc.type.qualificationlevel | Doctoral | en |
dc.type.qualificationname | PhD Doctor of Philosophy | en |