Dynamic Flexible Constraint Satisfaction and it's Application to AI Planning

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