Unveiling the properties of structured grammatical evolution
Abstract Structured grammatical evolution (SGE) is a new genotypic representation for grammatical evolution (GE). It comprises a hierarchical organization of the genes, where each locus is explicitly linked to a non-terminal of the grammar being used. This one-to-one correspondence ensures that the...
Ausführliche Beschreibung
Autor*in: |
Lourenço, Nuno [verfasserIn] |
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Artikel |
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Sprache: |
Englisch |
Erschienen: |
2016 |
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Anmerkung: |
© Springer Science+Business Media New York 2016 |
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Übergeordnetes Werk: |
Enthalten in: Genetic programming and evolvable machines - Springer US, 2000, 17(2016), 3 vom: 03. Feb., Seite 251-289 |
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Übergeordnetes Werk: |
volume:17 ; year:2016 ; number:3 ; day:03 ; month:02 ; pages:251-289 |
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DOI / URN: |
10.1007/s10710-015-9262-4 |
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OLC2039026878 |
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520 | |a Abstract Structured grammatical evolution (SGE) is a new genotypic representation for grammatical evolution (GE). It comprises a hierarchical organization of the genes, where each locus is explicitly linked to a non-terminal of the grammar being used. This one-to-one correspondence ensures that the modification of a gene does not affect the derivation options of other non-terminals. We present a comprehensive set of optimization results obtained with problems from three different categories: symbolic regression, path finding, and predictive modeling. In most of the situations SGE outperforms standard GE, confirming the effectiveness of the new representation. To understand the reasons for SGE enhanced performance, we scrutinize its main features. We rely on a set of static measures to model the interactions between the representation and variation operators and assess how they influence the interplay between the genotype-phenotype spaces. The study reveals that the structured organization of SGE promotes an increased locality and is less redundant than standard GE, thus fostering an effective exploration of the search space. | ||
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700 | 1 | |a Costa, Ernesto |4 aut | |
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10.1007/s10710-015-9262-4 doi (DE-627)OLC2039026878 (DE-He213)s10710-015-9262-4-p DE-627 ger DE-627 rakwb eng 004 VZ 54.72$jKünstliche Intelligenz bkl Lourenço, Nuno verfasserin (orcid)0000-0002-2154-0642 aut Unveiling the properties of structured grammatical evolution 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2016 Abstract Structured grammatical evolution (SGE) is a new genotypic representation for grammatical evolution (GE). It comprises a hierarchical organization of the genes, where each locus is explicitly linked to a non-terminal of the grammar being used. This one-to-one correspondence ensures that the modification of a gene does not affect the derivation options of other non-terminals. We present a comprehensive set of optimization results obtained with problems from three different categories: symbolic regression, path finding, and predictive modeling. In most of the situations SGE outperforms standard GE, confirming the effectiveness of the new representation. To understand the reasons for SGE enhanced performance, we scrutinize its main features. We rely on a set of static measures to model the interactions between the representation and variation operators and assess how they influence the interplay between the genotype-phenotype spaces. The study reveals that the structured organization of SGE promotes an increased locality and is less redundant than standard GE, thus fostering an effective exploration of the search space. Genetic programming Grammatical evolution Locality Redundancy Representation Pereira, Francisco B. aut Costa, Ernesto aut Enthalten in Genetic programming and evolvable machines Springer US, 2000 17(2016), 3 vom: 03. Feb., Seite 251-289 (DE-627)320647293 (DE-600)2025535-4 (DE-576)9320647291 1389-2576 nnns volume:17 year:2016 number:3 day:03 month:02 pages:251-289 https://doi.org/10.1007/s10710-015-9262-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.72$jKünstliche Intelligenz VZ 10641240X (DE-625)10641240X AR 17 2016 3 03 02 251-289 |
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Abstract Structured grammatical evolution (SGE) is a new genotypic representation for grammatical evolution (GE). It comprises a hierarchical organization of the genes, where each locus is explicitly linked to a non-terminal of the grammar being used. This one-to-one correspondence ensures that the modification of a gene does not affect the derivation options of other non-terminals. We present a comprehensive set of optimization results obtained with problems from three different categories: symbolic regression, path finding, and predictive modeling. In most of the situations SGE outperforms standard GE, confirming the effectiveness of the new representation. To understand the reasons for SGE enhanced performance, we scrutinize its main features. We rely on a set of static measures to model the interactions between the representation and variation operators and assess how they influence the interplay between the genotype-phenotype spaces. The study reveals that the structured organization of SGE promotes an increased locality and is less redundant than standard GE, thus fostering an effective exploration of the search space. © Springer Science+Business Media New York 2016 |
abstractGer |
Abstract Structured grammatical evolution (SGE) is a new genotypic representation for grammatical evolution (GE). It comprises a hierarchical organization of the genes, where each locus is explicitly linked to a non-terminal of the grammar being used. This one-to-one correspondence ensures that the modification of a gene does not affect the derivation options of other non-terminals. We present a comprehensive set of optimization results obtained with problems from three different categories: symbolic regression, path finding, and predictive modeling. In most of the situations SGE outperforms standard GE, confirming the effectiveness of the new representation. To understand the reasons for SGE enhanced performance, we scrutinize its main features. We rely on a set of static measures to model the interactions between the representation and variation operators and assess how they influence the interplay between the genotype-phenotype spaces. The study reveals that the structured organization of SGE promotes an increased locality and is less redundant than standard GE, thus fostering an effective exploration of the search space. © Springer Science+Business Media New York 2016 |
abstract_unstemmed |
Abstract Structured grammatical evolution (SGE) is a new genotypic representation for grammatical evolution (GE). It comprises a hierarchical organization of the genes, where each locus is explicitly linked to a non-terminal of the grammar being used. This one-to-one correspondence ensures that the modification of a gene does not affect the derivation options of other non-terminals. We present a comprehensive set of optimization results obtained with problems from three different categories: symbolic regression, path finding, and predictive modeling. In most of the situations SGE outperforms standard GE, confirming the effectiveness of the new representation. To understand the reasons for SGE enhanced performance, we scrutinize its main features. We rely on a set of static measures to model the interactions between the representation and variation operators and assess how they influence the interplay between the genotype-phenotype spaces. The study reveals that the structured organization of SGE promotes an increased locality and is less redundant than standard GE, thus fostering an effective exploration of the search space. © Springer Science+Business Media New York 2016 |
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title_short |
Unveiling the properties of structured grammatical evolution |
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https://doi.org/10.1007/s10710-015-9262-4 |
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author2 |
Pereira, Francisco B. Costa, Ernesto |
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Pereira, Francisco B. Costa, Ernesto |
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10.1007/s10710-015-9262-4 |
up_date |
2024-07-03T21:17:55.478Z |
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