Effects of Mutation before and after offspring selection in genetic programming for symbolic regression

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@InProceedings{Kronberger:2010:EMSS,
  author =       "Gabriel K. Kronberger and Stephan M. Winkler and 
                 Michael Affenzeller and Michael Kommenda and 
                 Stefan Wagner",
  title =        "Effects of Mutation before and after offspring
                 selection in genetic programming for symbolic
                 regression",
  booktitle =    "22nd European Modeling \& Simulation Symposium
                 (Simulation in Industry), EMSS 2010",
  year =         "2010",
  editor =       "Agostino Bruzzone and Claudia Frydman",
  address =      "Fes, Morocco",
  month =        oct # " 13-15",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://research.fh-ooe.at/en/publication/1879",
  size =         "6 pages",
  abstract =     "In evolutionary algorithms mutation operators increase
                 the genetic diversity in the population. Mutations are
                 undirected and have only a low probability to improve
                 the quality of the manipulated solution. Offspring
                 selection determines if a newly created solution is
                 added to the next generation of the population. By
                 definition, offspring selection is applied after
                 mutation and the effects of mutation are directed and
                 quality-driven. In this paper we propose an alternative
                 variant of genetic programming with offspring selection
                 where mutation is applied to increase genetic diversity
                 after offspring selection. We compare the solution
                 quality achieved by the original algorithm and the new
                 algorithm when applied to a symbolic regression
                 problem. We observe that solutions produced by the new
                 variant have a smaller generalisation error and
                 conclude that the proposed variant is better for
                 symbolic regression with linear scaling",
  notes =        "http://www.msc-les.org/conf/emss2010/index_file/EMSS10_Program.htm",
}

Genetic Programming entries for Gabriel Kronberger Stephan M Winkler Michael Affenzeller Michael Kommenda Stefan Wagner

Citations