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European Conference on Genetic Programming

EuroGP 2015: Genetic Programming pp 105–112Cite as

Attributed Grammatical Evolution Using Shared Memory Spaces and Dynamically Typed Semantic Function Specification

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9025))

Abstract

In this paper we introduce a new Grammatical Evolution (GE) system designed to support the specification of problem semantics in the form of attribute grammars (AG). We discuss the motivations behind our system design, from its use of shared memory spaces for attribute storage to the use of a dynamically type programming language, Python, to specify grammar semantics.

After a brief analysis of some of the existing GE AG system we outline two sets of experiments carried out on four symbolic regression type (SR) problems. The first set using a context free grammar (CFG) and second using an AG. After presenting the results of our experiments we highlight some of the potential areas for future performance improvements, using the new functionality that access to Python interpreter and storage of attributes in shared memory space provides.

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References

  1. de la Cruz Echeandía, M., de la Puente, A.O., Alfonseca, M.: Attribute grammar evolution. In: Mira, J., Álvarez, J.R. (eds.) IWINAC 2005. LNCS, vol. 3562, pp. 182–191. Springer, Heidelberg (2005)

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  2. Dempsey, I., O’Neill, M., Brabazon, A.: Constant creation in grammatical evolution. Int. J. Innov. Comput. Appl. 1(1), 23–38 (2007)

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  3. Karim, M.R., Ryan, C.: Sensitive ants are sensible ants. In: Proceedings of the Fourteenth International Conference on Genetic and Evolutionary Computation Conference, pp. 775–782. ACM (2012)

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  4. Keijzer, M.: Improving symbolic regression with interval arithmetic and linear scaling. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E., Poli, R., Costa, E. (eds.) EuroGP 2003. LNCS, vol. 2610, pp. 70–82. Springer, Heidelberg (2003)

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  5. Knuth, D.E.: Semantics of context-free languages. Math. Syst. Theory 2(2), 127–145 (1968)

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  6. O’Neill, M., Ryan, C.: Grammatical evolution: Evolutionary Automatic Programming in an Arbitrary Language. Kluwer, Boston (2003)

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Author information

Authors and Affiliations

  1. Biocomputing and Developmental Systems Group, University of Limerick, Limerick, Ireland

    James Vincent Patten & Conor Ryan

Authors
  1. James Vincent Patten
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  2. Conor Ryan
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Corresponding author

Correspondence to James Vincent Patten .

Editor information

Editors and Affiliations

  1. Universidade de Coimbra, Coimbra, Portugal

    Penousal Machado

  2. Dalhousie University, Halifax, Nova Scotia, Canada

    Malcolm I. Heywood

  3. University College Dublin, Dublin, Ireland

    James McDermott

  4. Universidade Nova de Lisboa, Lisboa, Portugal

    Mauro Castelli

  5. Universidad de Granada, Granada, Spain

    Pablo García-Sánchez

  6. Aalborg University, Copenhagen, Denmark

    Paolo Burelli

  7. IT University of Copenhagen, Copenhagen, Denmark

    Sebastian Risi

  8. Edinburgh Napier University, Edinburgh, United Kingdom

    Kevin Sim

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© 2015 Springer International Publishing Switzerland

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Patten, J.V., Ryan, C. (2015). Attributed Grammatical Evolution Using Shared Memory Spaces and Dynamically Typed Semantic Function Specification. In: Machado, P., et al. Genetic Programming. EuroGP 2015. Lecture Notes in Computer Science(), vol 9025. Springer, Cham. https://doi.org/10.1007/978-3-319-16501-1_9

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  • DOI: https://doi.org/10.1007/978-3-319-16501-1_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16500-4

  • Online ISBN: 978-3-319-16501-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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