How Effective are Multiple Populations in Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8178

@InProceedings{punch:1998:empGP,

• author = "William F. Punch",
• title = "How Effective are Multiple Populations in Genetic Programming",
• booktitle = "Genetic Programming 1998: Proceedings of the Third Annual Conference",
• year = "1998",
• editor = "John R. Koza and Wolfgang Banzhaf and Kumar Chellapilla and Kalyanmoy Deb and Marco Dorigo and David B. Fogel and Max H. Garzon and David E. Goldberg and Hitoshi Iba and Rick Riolo",
• pages = "308--313",
• address = "University of Wisconsin, Madison, Wisconsin, USA",
• publisher_address = "San Francisco, CA, USA",
• month = "22-25 " # jul,
• publisher = "Morgan Kaufmann",
• keywords = "genetic algorithms, genetic programming, parallel computing, royal trees sequence problem, deceptive",
• ISBN = "1-55860-548-7",
• URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/gp1998/punch_1998_empGP.pdf",
• size = "6 pages",
• abstract = "The use of multiple populations in Genetic Programming is an area that is just beginning to be investigated. To date a number of conflicting reports have been generated with respect to the effectiveness of multiple populations in GP. We report here that these conflicting reports may be due a problem-dependent nature found in GP that has not been reported in GAs. This paper will review: what both multiple populations and speed-up mean in the areas of GA/GP, some conflicting results that have been reported in the GP literature on whether multiple populations gives speed-up to GP problems, and offer an answer as to why different GP problems show different kinds of speed-up when using multiple populations.",
• notes = "GP-98",

}

Genetic Programming entries for William F Punch

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