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@InProceedings{DBLP:conf/sac/DolinBR02, author = "Brad Dolin and Forrest H. Bennett III and Eleanor G. Rieffel", title = "Co-evolving an effective fitness sample: experiments in symbolic regression and distributed robot control", booktitle = "Proceedings of the 2002 ACM Symposium on Applied Computing (SAC)", year = "2002", pages = "553--559", address = "Madrid, Spain", month = mar # " 10-14", publisher = "ACM", bibsource = "DBLP, http://dblp.uni-trier.de", keywords = "genetic algorithms, genetic programming, co-evolution, fitness cases, symbolic regression, robot control, distributed control", ISBN = "1-58113-445-2", DOI = "doi:10.1145/508791.508899", abstract = "We investigate two techniques for co-evolving and sampling from a population of fitness cases, and compare these with a random sampling technique. We design three symbolic regression problems on which to test these techniques, and also measure their relative performance on a modular robot control problem. The methods have varying relative performance, but in all of our experiments, at least one of the co-evolutionary methods outperforms the random sampling method by guiding evolution, with substantially fewer fitness evaluations, toward solutions that generalize best on an out-of-sample test set.", }
Genetic Programming entries for Brad Dolin Forrest Bennett Eleanor G Rieffel