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Studying Grammatical Evolution’s Mapping Processes for Symbolic Regression Problems

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Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 862))

Abstract

Grammatical Evolution (GE) is a variant of Genetic Programming (GP) that uses a BNF-grammar to create syntactically correct solutions. GE is composed of the following components: the Problem Instance, the BNF-grammar (BNF), the Search Engine (SE) and the Mapping Process (MP). GE allows creating a distinction between the solution and search spaces using an MP and the BNF to translate from genotype to phenotype, that avoids invalid solutions that can be obtained with GP. One genotype can generate different phenotypes using a different MP. There exist at least three MPs widely used in the art-state: Depth-first (DF), Breadth-first (BF) and \( \pi \)Grammatical Evolution (piGE). In the present work DF, BF, and piGE have been studied in the Symbolic Regression Problem. The results were compared using a statistical test to determine which MP gives the best results.

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Acknowledgements

The authors want to thank National Council for Science and Technology of Mexico (CONACyT) through the scholarship for postgraduate studies: 703582 (B. Zuñiga) and the Research Grant CÁTEDRAS-2598 (A. Rojas), the Leín Institute of Technology (ITL), and the Guanajuato University for the support provided for this research.

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Authors and Affiliations

  1. Departamento de Estudios de Posgrado e Investigación, Tecnológico Nacional de México, Instituto Tecnológico de León, Avenida Tecnológico S/N, 37290, León, GTO, México

    B. V. Zuñiga-Nuñez, J. Martín Carpio, Manuel Ornelas & A. Rojas-Domínguez

  2. División de Ciencias Económico Administrativas, Departamento de Estudios Organizacionales, Universidad de Guanajuato, Fraccionamiento I El Establo, 36250, Guanajuato, GTO, México

    M. A. Sotelo-Figueroa, J. A. Soria-Alcaraz & O. J. Purata-Sifuentes

Authors
  1. B. V. Zuñiga-Nuñez
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  2. J. Martín Carpio
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  3. M. A. Sotelo-Figueroa
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  4. J. A. Soria-Alcaraz
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  5. O. J. Purata-Sifuentes
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  6. Manuel Ornelas
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  7. A. Rojas-Domínguez
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Corresponding author

Correspondence to M. A. Sotelo-Figueroa .

Editor information

Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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Zuñiga-Nuñez, B.V. et al. (2020). Studying Grammatical Evolution’s Mapping Processes for Symbolic Regression Problems. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications. Studies in Computational Intelligence, vol 862. Springer, Cham. https://doi.org/10.1007/978-3-030-35445-9_32

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