poster

Structural and nodal mutation in grammatical evolution

Authors:

Jonathan Byrne,

Michael O'Neill,

Anthony BrabazonAuthors Info & Claims

GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation

Pages 1881 - 1882

https://doi.org/10.1145/1569901.1570215

Published: 08 July 2009 Publication History

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Abstract

This study focuses on mutation in Grammatical Evolution and divides mutation events into those that are structural in nature and those that are nodal. A structural event being one that alters the length of the phenotype. A nodal event simply alters the value at any node of a derivation tree. We analyse and compare the effect of integer, nodal and structural mutations on fitness for randomly generated individuals before continuing this analysis to their relative problem-solving performance over full runs. The study highlights the importance of understanding how the search operators of an evolutionary algorithm behave. The result in this case being a form of mutation for Grammatical Evolution, node mutation, with a better property of locality than standard integer-based mutation, which does not discriminate between structural and nodal contexts.

References

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[2]

O'Neill, M., Ryan, C. (2003).Grammatical Evolution. Kluwer Academic Publishers.

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[3]

O'Neill M., Ryan C., Keijzer M., Cattolico M. (2003). Crossover in Grammatical Evolution. Genetic Programming and Evolvable Machines.4(1):67--93.

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Harper R., Blair A. (2005). A Structure Preserving Crossover in Grammatical Evolution. In Proc. CEC 2005, Vol.3, pp.2537--2544. IEEE Press.

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Cited By

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Kunaver MBűrmen ÁFajfar I(2022)Automatic Grammatical Evolution-Based Optimization of Matrix Factorization AlgorithmMathematics10.3390/math1007113910:7(1139)Online publication date: 1-Apr-2022
https://doi.org/10.3390/math10071139
Fajfar IB?Rmen ÁPuhan J(2018)Grammatical evolution as a hyper-heuristic to evolve deterministic real-valued optimization algorithmsGenetic Programming and Evolvable Machines10.1007/s10710-018-9324-519:4(473-504)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s10710-018-9324-5
Lourenço NAssunção FPereira FCosta EMachado P(2018)Structured Grammatical Evolution: A Dynamic ApproachHandbook of Grammatical Evolution10.1007/978-3-319-78717-6_6(137-161)Online publication date: 12-Sep-2018
https://doi.org/10.1007/978-3-319-78717-6_6
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Index Terms

Structural and nodal mutation in grammatical evolution
1. Theory of computation
  1. Formal languages and automata theory
    1. Formalisms
      1. Rewrite systems
    2. Grammars and context-free languages

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Information & Contributors

Information

Published In

GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation

July 2009

2036 pages

ISBN:9781605583259

DOI:10.1145/1569901

General Chair:
Franz Rothlauf
University of Mainz, Germany

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 July 2009

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GECCO09

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GECCO09: Genetic and Evolutionary Computation Conference

July 8 - 12, 2009

Québec, Montreal, Canada

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

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Kunaver MBűrmen ÁFajfar I(2022)Automatic Grammatical Evolution-Based Optimization of Matrix Factorization AlgorithmMathematics10.3390/math1007113910:7(1139)Online publication date: 1-Apr-2022
https://doi.org/10.3390/math10071139
Fajfar IB?Rmen ÁPuhan J(2018)Grammatical evolution as a hyper-heuristic to evolve deterministic real-valued optimization algorithmsGenetic Programming and Evolvable Machines10.1007/s10710-018-9324-519:4(473-504)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s10710-018-9324-5
Lourenço NAssunção FPereira FCosta EMachado P(2018)Structured Grammatical Evolution: A Dynamic ApproachHandbook of Grammatical Evolution10.1007/978-3-319-78717-6_6(137-161)Online publication date: 12-Sep-2018
https://doi.org/10.1007/978-3-319-78717-6_6
Fenton MMcDermott JFagan DForstenlechner SHemberg EO'Neill M(2017)PonyGE2Proceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3067695.3082469(1194-1201)Online publication date: 15-Jul-2017
https://dl.acm.org/doi/10.1145/3067695.3082469
Whigham PDick GMaclaurin J(2017)On the mapping of genotype to phenotype in evolutionary algorithmsGenetic Programming and Evolvable Machines10.1007/s10710-017-9288-x18:3(353-361)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1007/s10710-017-9288-x
Lourenço NFerrer JPereira FCosta E(2017)A Comparative Study of Different Grammar-Based Genetic Programming ApproachesGenetic Programming10.1007/978-3-319-55696-3_20(311-325)Online publication date: 15-Mar-2017
https://doi.org/10.1007/978-3-319-55696-3_20
Lourenço NPereira FCosta E(2016)Unveiling the properties of structured grammatical evolutionGenetic Programming and Evolvable Machines10.1007/s10710-015-9262-417:3(251-289)Online publication date: 1-Sep-2016
https://dl.acm.org/doi/10.1007/s10710-015-9262-4
Thorhauer ARothlauf F(2014)On the Locality of Standard Search Operators in Grammatical EvolutionParallel Problem Solving from Nature – PPSN XIII10.1007/978-3-319-10762-2_46(465-475)Online publication date: 2014
https://doi.org/10.1007/978-3-319-10762-2_46
Lopes RCosta EAlba E(2013)GEARNetProceedings of the 15th annual conference on Genetic and evolutionary computation10.1145/2463372.2463490(973-980)Online publication date: 6-Jul-2013
https://dl.acm.org/doi/10.1145/2463372.2463490
Byrne JHemberg EO'Neill MBrabazon A(2013)A methodology for user directed search in evolutionary designGenetic Programming and Evolvable Machines10.1007/s10710-013-9189-614:3(287-314)Online publication date: 1-Sep-2013
https://dl.acm.org/doi/10.1007/s10710-013-9189-6
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