Genetic Programming with Epigenetic Local Search

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{LaCava:2015:GECCO,

• author = "William {La Cava} and Thomas Helmuth and Lee Spector and Kourosh Danai",
• title = "Genetic Programming with Epigenetic Local Search",
• booktitle = "GECCO '15: Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation",
• year = "2015",
• 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",
• isbn13 = "978-1-4503-3472-3",
• pages = "1055--1062",
• keywords = "genetic algorithms, genetic programming",
• month = "11-15 " # jul,
• organisation = "SIGEVO",
• address = "Madrid, Spain",
• URL = "http://doi.acm.org/10.1145/2739480.2754763",
• DOI = "doi:10.1145/2739480.2754763",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• 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.",
• 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