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A SAT-Based Version Space Algorithm for Acquiring Constraint Satisfaction Problems

  • Christian Bessiere
  • Remi Coletta
  • Frédéric Koriche
  • Barry O’Sullivan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3720)

Abstract

Constraint programming is rapidly becoming the technology of choice for modelling and solving complex combinatorial problems. However, users of this technology need significant expertise in order to model their problems appropriately. The lack of availability of such expertise is a significant bottleneck to the broader uptake of constraint technology in the real world. We present a new SAT-based version space algorithm for acquiring constraint satisfaction problems from examples of solutions and non-solutions of a target problem. An important advantage is the ease with which domain-specific knowledge can be exploited using the new algorithm. Finally, we empirically demonstrate the algorithm and the effect of exploiting domain-specific knowledge on improving the quality of the acquired constraint network.

Keywords

Version Space Constraint Programming Constraint Satisfaction Problem Horn Clause Constraint Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Christian Bessiere
    • 1
  • Remi Coletta
    • 1
  • Frédéric Koriche
    • 1
  • Barry O’Sullivan
    • 2
  1. 1.LIRMM, CNRS / U. MontpellierMontpellierFrance
  2. 2.Cork Constraint Computation CentreUniversity College CorkIreland

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