An Efficient Structural Diversity Technique for Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{Burks:2015:GECCO,
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author = "Armand R. Burks and William F. Punch",
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title = "An Efficient Structural Diversity Technique for
Genetic Programming",
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booktitle = "GECCO '15: Proceedings of the 2015 Annual Conference
on Genetic and Evolutionary Computation",
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year = "2015",
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editor = "Sara Silva and Anna I Esparcia-Alcazar and
Manuel Lopez-Ibanez and Sanaz Mostaghim and Jon Timmis and
Christine Zarges and Luis Correia and Terence Soule and
Mario Giacobini and Ryan Urbanowicz and
Youhei Akimoto and Tobias Glasmachers and
Francisco {Fernandez de Vega} and Amy Hoover and Pedro Larranaga and
Marta Soto and Carlos Cotta and Francisco B. Pereira and
Julia Handl and Jan Koutnik and Antonio Gaspar-Cunha and
Heike Trautmann and Jean-Baptiste Mouret and
Sebastian Risi and Ernesto Costa and Oliver Schuetze and
Krzysztof Krawiec and Alberto Moraglio and
Julian F. Miller and Pawel Widera and Stefano Cagnoni and
JJ Merelo and Emma Hart and Leonardo Trujillo and
Marouane Kessentini and Gabriela Ochoa and Francisco Chicano and
Carola Doerr",
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isbn13 = "978-1-4503-3472-3",
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pages = "991--998",
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keywords = "genetic algorithms, genetic programming",
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month = "11-15 " # jul,
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organisation = "SIGEVO",
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address = "Madrid, Spain",
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URL = "http://doi.acm.org/10.1145/2739480.2754649",
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DOI = "doi:10.1145/2739480.2754649",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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abstract = "Genetic diversity plays an important role in avoiding
premature convergence, which is a phenomenon that
stifles the search effectiveness of evolutionary
algorithms. However, approaches that avoid premature
convergence by maintaining genetic diversity can do so
at the cost of efficiency, requiring more fitness
evaluations to find high quality solutions. We
introduce a simple and efficient genetic diversity
technique that is capable of avoiding premature
convergence while maintaining a high level of search
quality in tree-based genetic programming. Our method
finds solutions to a set of benchmark problems in
significantly fewer fitness evaluations than the
algorithms that we compared against.",
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notes = "Also known as \cite{2754649} GECCO-2015 A joint
meeting of the twenty fourth international conference
on genetic algorithms (ICGA-2015) and the twentith
annual genetic programming conference (GP-2015)",
- }
Genetic Programming entries for
Armand R Burks
William F Punch
Citations