Code Regulation in Open Ended Evolution

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

@InProceedings{eurogp07:yamamoto,
  author =       "Lidia Yamamoto",
  title =        "Code Regulation in Open Ended Evolution",
  editor =       "Marc Ebner and Michael O'Neill and Anik\'o Ek\'art and 
                 Leonardo Vanneschi and Anna Isabel Esparcia-Alc\'azar",
  booktitle =    "Proceedings of the 10th European Conference on Genetic
                 Programming",
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  volume =       "4445",
  year =         "2007",
  address =      "Valencia, Spain",
  month =        "11-13 " # apr,
  pages =        "271--280",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-71602-5",
  isbn13 =       "978-3-540-71602-0",
  DOI =          "doi:10.1007/978-3-540-71605-1_25",
  abstract =     "We explore a homoeostatic approach to program
                 execution in computer systems: the 'concentration' of
                 computation services is regulated according to their
                 fitness. The goal is to obtain a self-healing effect so
                 that the system can resist harmful mutations that could
                 happen during on-line evolution. We present a model in
                 which alternative program variants are stored in a
                 repository representing the organism's 'genotype'.
                 Positive feedback signals allow code in the repository
                 to be expressed (in analogy to gene expression in
                 biology), meaning that it is injected into a reaction
                 vessel (execution environment) where it is executed and
                 evaluated. Since execution is equivalent to a chemical
                 reaction, the program is consumed in the process,
                 therefore needs more feedback in order to be
                 re-expressed. This leads to services that constantly
                 regulate themselves to a stable condition given by the
                 fitness feedback received from the users or the
                 environment. We present initial experiments using this
                 model, implemented using a chemical computing
                 language.",
  notes =        "Part of \cite{ebner:2007:GP} EuroGP'2007 held in
                 conjunction with EvoCOP2007, EvoBIO2007 and
                 EvoWorkshops2007",
}

Genetic Programming entries for Lidia Yamamoto

Citations