Effects of Mutation before and after offspring selection in genetic programming for symbolic regression
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Kronberger:2010:EMSS,
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author = "Gabriel K. Kronberger and Stephan M. Winkler and
Michael Affenzeller and Michael Kommenda and
Stefan Wagner",
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title = "Effects of Mutation before and after offspring
selection in genetic programming for symbolic
regression",
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booktitle = "22nd European Modeling \& Simulation Symposium
(Simulation in Industry), EMSS 2010",
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year = "2010",
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editor = "Agostino Bruzzone and Claudia Frydman",
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address = "Fes, Morocco",
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month = oct # " 13-15",
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keywords = "genetic algorithms, genetic programming",
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URL = "http://research.fh-ooe.at/en/publication/1879",
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size = "6 pages",
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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",
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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