Imitating Success: A Memetic Crossover Operator for Genetic Programming

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

@InProceedings{eskridge:2004:isamcofgp,

• title = "Imitating Success: A Memetic Crossover Operator for Genetic Programming",
• author = "Brent Eskridge and Dean Hougen",
• pages = "809--815",
• 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, Theory of evolutionary algorithms, Poster Session",
• DOI = "doi:10.1109/CEC.2004.1330943",
• abstract = "For some problem domains, the evaluation of individuals is significantly more expensive than the other steps in the evolutionary process. Minimizing these evaluations is vital if we want to make genetic programming a viable strategy. In order to minimize the required evaluations, we need to maximize the amount learned from each evaluation. To accomplish this we introduce a new crossover operator for genetic programming, memetic crossover, that allows individuals to imitate the observed success of others. An individual that has done poorly in some parts of the problem may then imitate an individual that did well on those same parts. This results in an intelligent search of the feature-space and, therefore, fewer evaluations.",
• notes = "CEC 2004 - A joint meeting of the IEEE, the EPS, and the IEE.",

}

Genetic Programming entries for Brent E Eskridge Dean F Hougen

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