Predicting optimal constraint satisfaction methods

Authors:
Craig D S. Thompson
Affiliations:
Department of Computer Science, University of Saskatchewan, Saskatoon, Canada
Venue:
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
Year:
2010

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Abstract

Given the breadth of constraint satisfaction problems (CSP) and the wide variety of CSP solvers, it is often very difficult to determine a priori which solving method is best suited to a problem This work explores the use of machine learning to predict which solving method will be most effective for a given problem.