Genetic Programming with Epigenetic Local Search
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{LaCava:2015:GECCO,
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author = "William {La Cava} and Thomas Helmuth and
Lee Spector and Kourosh Danai",
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title = "Genetic Programming with Epigenetic Local Search",
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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 = "1055--1062",
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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/10.1145/2739480.2754763",
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DOI = "doi:10.1145/2739480.2754763",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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abstract = "We focus on improving genetic programming through
local search of the space of program structures using
an inheritable epigenetic layer that specifies active
and inactive genes. We explore several genetic
programming implementations that represent the
different properties that epigenetics can provide, such
as passive structure, phenotypic plasticity, and
inheritable gene regulation. We apply these
implementations to several symbolic regression and
program synthesis problems. For the symbolic regression
problems, the results indicate that epigenetic local
search consistently improves genetic programming by
producing smaller solution programs with better
fitness. Furthermore, we find that incorporating
epigenetic modification as a mutation step in program
synthesis problems can improve the ability of genetic
programming to find exact solutions. By analyzing
population homology we show that the epigenetic
implementations maintain diversity in silenced portions
of programs which may provide protection from premature
convergence.",
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notes = "Also known as \cite{2754763} 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
William La Cava
Thomas Helmuth
Lee Spector
Kourosh Danai
Citations