Learning Implied Global Constraints - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Conference Papers Year : 2007

Learning Implied Global Constraints

Remi Coletta
  • Function : Author
  • PersonId : 932759
LRD
Thierry Petit

Abstract

Finding a constraint network that will be efficiently solved by a constraint solver requires a strong expertise in Constraint Programming. Hence, there is an increasing interest in automatic reformulation. This paper presents a general framework for learning implied global constraints in a constraint network assumed to be provided by a non-expert user. The learned global constraints can then be added to the network to improve the solving process. We apply our technique to global cardinality constraints. Experiments show the significance of the approach.

Domains

Other
No file

Dates and versions

lirmm-00195896 , version 1 (11-12-2007)

Identifiers

  • HAL Id : lirmm-00195896 , version 1

Cite

Christian Bessiere, Remi Coletta, Thierry Petit. Learning Implied Global Constraints. IJCAI'07: International Joint Conference on Artificial Intelligence, 2007, Hyderabad, India. pp.50-55. ⟨lirmm-00195896⟩
221 View
0 Download

Share

Gmail Facebook X LinkedIn More