Genetic Programming with Epigenetic Local Search

Created by W.Langdon from gp-bibliography.bib Revision:1.4496

  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 =          "",
  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
  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