Loading ...
Sorry, an error occurred while loading the content.

Reference information for seminal GEP paper

Expand Messages
  • Candida Ferreira
    Dear all, Please update the reference information for my paper: Ferreira, C., (2001). Gene Expression Programming: A New Adaptive Algorithm for Solving
    Message 1 of 2 , Dec 5, 2001
    • 0 Attachment
      Dear all,

      Please update the reference information for my paper:
      Ferreira, C., (2001). Gene Expression Programming: A New Adaptive Algorithm for Solving Problems, Complex Systems, 13 (2): 87 - 129.

      The paper is available at:

      http://www.gene-expression-programming.com/webpapers/gep.pdf

      ABSTRACT:
      Gene expression programming, a genotype/phenotype genetic algorithm (linear and ramified), is presented here for the first time as a new technique for the creation of computer programs. Gene expression programming uses character linear chromosomes composed of genes structurally organized in a head and a tail. The chromosomes function as a genome and are subjected to modification by means of mutation, transposition, root transposition, gene transposition, gene recombination, and one- and two-point recombination. The chromosomes encode expression trees which are the object of selection. The creation of these separate entities (genome and expression tree) with distinct functions allows the algorithm to perform with high efficiency that greatly surpasses existing adaptive techniques. The suite of problems chosen to illustrate the power and versatility of gene expression programming includes symbolic regression, sequence induction with and without constant creation, block stacking, cellular automata rules for the density-classification problem, and two problems of boolean concept learning: the 11-multiplexer and the GP rule problem.

      Best regards,
      Candida Ferreira

      ++++++++++++++++++++++++++++++++++++++++++
      Dr Candida Ferreira, Chief Scientist
      Gepsoft, 37 The Ridings, Bristol BS13 8NU, UK
      candidaf@..., tel: +44 (0) 117 907 1668
      http://www.gepsoft.com
      ++++++++++++++++++++++++++++++++++++++++++
    • Bill Mydlowec
      http://www.wikipedia.com/wiki/Sokal_Affair ... From: Candida Ferreira Sent: Wed Dec 5, 2001 10:33 pm To: genetic_programming@yahoogroups.com Subject:
      Message 2 of 2 , Dec 9, 2001
      • 0 Attachment
        http://www.wikipedia.com/wiki/Sokal_Affair




        -----Original Message-----
        From: Candida Ferreira
        Sent: Wed Dec 5, 2001 10:33 pm
        To: genetic_programming@yahoogroups.com
        Subject: Reference information for seminal GEP paper



        Dear all,

        Please update the reference information for my paper:
        Ferreira, C., (2001). Gene Expression Programming: A New Adaptive
        Algorithm for
        Solving Problems, Complex Systems, 13 (2): 87 - 129.

        The paper is available at:

        http://www.gene-expression-programming.com/webpapers/gep.pdf

        ABSTRACT:
        Gene expression programming, a genotype/phenotype genetic algorithm
        (linear and
        ramified), is presented here for the first time as a new technique for the
        creation of computer programs. Gene expression programming uses character
        linear chromosomes composed of genes structurally organized in a head and
        a
        tail. The chromosomes function as a genome and are subjected to
        modification by
        means of mutation, transposition, root transposition, gene transposition,
        gene
        recombination, and one- and two-point recombination. The chromosomes
        encode
        expression trees which are the object of selection. The creation of these
        separate entities (genome and expression tree) with distinct functions
        allows
        the algorithm to perform with high efficiency that greatly surpasses
        existing
        adaptive techniques. The suite of problems chosen to illustrate the power
        and
        versatility of gene expression programming includes symbolic regression,
        sequence induction with and without constant creation, block stacking,
        cellular
        automata rules for the density-classification problem, and two problems of
        boolean concept learning: the 11-multiplexer and the GP rule problem.

        Best regards,
        Candida Ferreira

        ++++++++++++++++++++++++++++++++++++++++++
        Dr Candida Ferreira, Chief Scientist
        Gepsoft, 37 The Ridings, Bristol BS13 8NU, UK
        candidaf@g..., tel: +44 (0) 117 907 1668
        http://www.gepsoft.com
        ++++++++++++++++++++++++++++++++++++++++++
      Your message has been successfully submitted and would be delivered to recipients shortly.