A reactive constraint programming formulation

Eric Monfroy, Carlos Castro, BRODERICK CRAWFORD LABRIN

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Constraint Programming is a powerful paradigm for solving Combinatorial Problems. In this solver approach, Enumeration Strategies are crucial for resolution performances. In a previous work, we proposed a framework to reactively change strategies showing bad performances, and to use metabacktracks to restore better states when bad decisions were made. In this paper, we design and evaluate strategies to improve resolution performances of a set of problems. Experimental results show the effectiveness of our approach.

Original languageEnglish
Title of host publication8th Mexican International Conference on Artificial Intelligence - Proceedings of the Special Session, MICAI 2009
Pages165-169
Number of pages5
DOIs
StatePublished - 1 Dec 2009
Event8th Mexican International Conference on Artificial Intelligence, MICAI 2009 - Guanajuato, Guanajuato, Mexico
Duration: 9 Nov 200913 Nov 2009

Publication series

Name8th Mexican International Conference on Artificial Intelligence - Proceedings of the Special Session, MICAI 2009

Conference

Conference8th Mexican International Conference on Artificial Intelligence, MICAI 2009
CountryMexico
CityGuanajuato, Guanajuato
Period9/11/0913/11/09

Keywords

  • Constraint programming
  • Constraint satisfaction problems
  • Enumeration strategies
  • Reactive search

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