Grammatical Evolution: Evolutionary Automatic Programming in a Arbitrary Language

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Michael O'Neill and Conor Ryan",
  title =        "Grammatical Evolution: Evolutionary Automatic
                 Programming in a Arbitrary Language",
  publisher =    "Kluwer Academic Publishers",
  year =         "2003",
  volume =       "4",
  series =       "Genetic programming",
  keywords =     "genetic algorithms, genetic programming, grammatical
  ISBN =         "1-4020-7444-1",
  URL =          "",
  DOI =          "doi:10.1007/978-1-4615-0447-4",
  abstract =     "Preface:

                 Since man began to dream of machines that could
                 automate not only the more mundane and laborious tasks
                 of everyday life, but that could also improve some of
                 the more agreeable aspects, he has turned to nature for
                 inspiration. This inspiration has taken all sorts of
                 forms, with inventors producing everything from
                 Icarus-like, bird-inspired flying machines to robots
                 based on some of the more mechanically useful human

                 Another inspiration that can be taken from nature is to
                 employ its tools, rather than necessarily employing its
                 products. In this way, the field of evolutionary
                 computation has taken stock of the power of evolution,
                 and applied it, albeit at a very coarse level, to
                 problem solving. Genetic Programming, a powerful
                 incarnation of evolutionary computation uses the
                 artificial evolutionary process to automatically
                 generate programs. The adoption of evolution to
                 automatic generation of programs represents one of the
                 most promising approaches to that holy grail of
                 computer science, automatic programming, that is, a
                 computer that can automatically generate a program from
                 scratch given a high-level problem

                 Research in Genetic Programming has explored a number
                 of program representations beyond the original Lisp
                 S-expression syntax trees, and some of the more
                 powerful of these incorporate a developmental strategy
                 that transforms an embryonic state into a fully fledged
                 adult program.

                 The form of Genetic Programming presented in this book,
                 Grammatical Evolution, delves further into nature's
                 processes at a molecular level, embracing the
                 developmental approach, and drawing upon a number of
                 principles that allow an abstract representation of a
                 program to be evolved.

                 This abstraction enables firstly, a separation of the
                 search and solution spaces that allow the EA search
                 engine to be a plug-in component of the system,
                 facilitating the exploitation of advances in EAs by GE.
                 Secondly, this allows the evolution of programs in an
                 arbitrary language with the representation of a
                 program's syntax in the form of a grammar

                 Thirdly, the existence of a degenerate genetic code is
                 enabled, giving a many-to-one mapping, that allows the
                 exploitation of neutral evolution to enhance the search
                 efficiency of the EA. Fourthly, we can adopt the use of
                 a wrapping operator that allows the reuse of genetic
                 material during a genotype-phenotype mapping

                 This book is partly based on the Ph.D. thesis of
                 Michael O'Neill, and reports a number of new directions
                 in Grammatical Evolution research that are been
                 conducted both within the confines of the University of
                 Limerick's Biocomputing-Developmental Systems Centre
                 where the book's authors reside, and also developments
                 that are occurring through collaborations around the

Genetic Programming entries for Michael O'Neill Conor Ryan