Reassembling operator equalisation: a secret revealed

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

@InProceedings{Silva:2011:GECCO,

• author = "Sara Silva",
• title = "Reassembling operator equalisation: a secret revealed",
• booktitle = "GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation",
• year = "2011",
• editor = "Natalio Krasnogor and Pier Luca Lanzi and Andries Engelbrecht and David Pelta and Carlos Gershenson and Giovanni Squillero and Alex Freitas and Marylyn Ritchie and Mike Preuss and Christian Gagne and Yew Soon Ong and Guenther Raidl and Marcus Gallager and Jose Lozano and Carlos Coello-Coello and Dario Landa Silva and Nikolaus Hansen and Silja Meyer-Nieberg and Jim Smith and Gus Eiben and Ester Bernado-Mansilla and Will Browne and Lee Spector and Tina Yu and Jeff Clune and Greg Hornby and Man-Leung Wong and Pierre Collet and Steve Gustafson and Jean-Paul Watson and Moshe Sipper and Simon Poulding and Gabriela Ochoa and Marc Schoenauer and Carsten Witt and Anne Auger",
• isbn13 = "978-1-4503-0557-0",
• pages = "1395--1402",
• keywords = "genetic algorithms, genetic programming",
• month = "12-16 " # jul,
• organisation = "SIGEVO",
• address = "Dublin, Ireland",
• DOI = "doi:10.1145/2001576.2001764",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• abstract = "The recent Crossover Bias theory has shown that bloat in Genetic Programming can be caused by the proliferation of small unfit individuals in the population. Inspired by this theory, Operator Equalisation is the most recent and successful bloat control method available. In this work we revisit two bloat control methods, the old Brood Recombination and the newer Dynamic Limits, hypothesizing that together they contain the two main ingredients that make Operator Equalisation so successful. We reassemble Operator Equalisation by joining these two ingredients in a hybrid method, and test it in a hard real world regression problem. The results are surprising. Operator Equalisation and the hybrid variants exhibit completely different behaviors, and an unexpected feature of Operator Equalisation is revealed, one that may be the true responsible for its success: a nearly flat length distribution target. We support this finding with additional results, and discuss its implications.",
• notes = "Also known as \cite{2001764} GECCO-2011 A joint meeting of the twentieth international conference on genetic algorithms (ICGA-2011) and the sixteenth annual genetic programming conference (GP-2011)",

}

Genetic Programming entries for Sara Silva

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