Evolving Algorithms for Constraint Satisfaction

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{bain:2004:eafcs,

• title = "Evolving Algorithms for Constraint Satisfaction",
• author = "Stuart Bain and John Thornton and Abdul Sattar",
• pages = "265--272",
• booktitle = "Proceedings of the 2004 IEEE Congress on Evolutionary Computation",
• year = "2004",
• publisher = "IEEE Press",
• month = "20-23 " # jun,
• address = "Portland, Oregon",
• ISBN = "0-7803-8515-2",
• keywords = "genetic algorithms, genetic programming, Combinatorial \& numerical optimization",
• URL = "http://stuart.multics.org/publications/CEC2004.pdf",
• URL = "https://research-repository.griffith.edu.au/bitstream/handle/10072/2138/27736.pdf",
• DOI = "doi:10.1109/CEC.2004.1330866",
• size = "8 pages",
• abstract = "This paper proposes a framework for automatically evolving constraint satisfaction algorithms using genetic programming. The aim is to overcome the difficulties associated with matching algorithms to specific constraint satisfaction problems. A representation is introduced that is suitable for genetic programming and that can handle both complete and local search heuristics. In addition, the representation is shown to have considerably more flexibility than existing alternatives, being able to discover entirely new heuristics and to exploit synergies between heuristics. In a preliminary empirical study it is shown that the new framework is capable of evolving algorithms for solving the well-studied problem of boolean satisfiability testing.",
• notes = "CEC 2004 - A joint meeting of the IEEE, the EPS, and the IEE.",

}

Genetic Programming entries for Stuart Bain John Thornton Abdul Sattar

Citations