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

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Patten:2015:EuroGP,
  author =       "James Vincent Patten and Conor Ryan",
  title =        "Attributed Grammatical Evolution using Shared Memory
                 Spaces and Dynamically Typed Semantic Function
                 Specification",
  booktitle =    "18th European Conference on Genetic Programming",
  year =         "2015",
  editor =       "Penousal Machado and Malcolm I. Heywood and 
                 James McDermott and Mauro Castelli and 
                 Pablo Garcia-Sanchez and Paolo Burelli and Sebastian Risi and Kevin Sim",
  series =       "LNCS",
  volume =       "9025",
  publisher =    "Springer",
  pages =        "105--112",
  address =      "Copenhagen",
  month =        "8-10 " # apr,
  organisation = "EvoStar",
  keywords =     "genetic algorithms, genetic programming, Grammatical
                 Evolution, Symbolic regression, Attribute grammars",
  isbn13 =       "978-3-319-16500-4",
  DOI =          "doi:10.1007/978-3-319-16501-1_9",
  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.",
  notes =        "Nominated for EuroGP 2015 Best Paper.

                 Part of \cite{Machado:2015:GP} EuroGP'2015 held in
                 conjunction with EvoCOP2015, EvoMusArt2015 and
                 EvoApplications2015",
}

Genetic Programming entries for James Vincent Patten Conor Ryan

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