Designing artificial organisms for use in biological simulations

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Ashlock:2011:CIBCB,
  author =       "Wendy Ashlock and Daniel Ashlock",
  title =        "Designing artificial organisms for use in biological
                 simulations",
  booktitle =    "IEEE Symposium on Computational Intelligence in
                 Bioinformatics and Computational Biology (CIBCB 2011)",
  year =         "2011",
  month =        "11-15 " # apr,
  address =      "Paris",
  size =         "8 pages",
  abstract =     "In this paper we investigate two types of artificial
                 organism which have the potential to be useful in
                 biological simulations at the genomic level, such as
                 simulations of speciation or gene interaction.
                 Biological problems of this type are usually studied
                 either with simulations using artificial genes that are
                 merely evolving strings with no phenotype, ignoring the
                 possibly crucial contribution of natural selection, or
                 with real biological data involving so much complexity
                 that it is difficult to sort out the important factors.
                 This research provides a middle ground. The artificial
                 organisms are: gridwalkers (GWs), a variation on the
                 self-avoiding walk problem, and plus-one-recall-store
                 (PORS), a simple genetic programming maximum problem
                 implemented with a context free grammar. Both are known
                 to have rugged multimodal fitness landscapes. We define
                 a new variation operator, a kind of aligned crossover
                 for variable length strings, which we call
                 Smith-Waterman crossover. The problems, using
                 Smith-Waterman crossover, size-neutral crossover (a
                 kind of non-aligned crossover defined in), mutation
                 only, and horizontal gene transfer (such as occurs in
                 biology with retroviruses) are explored. We define a
                 measure called fitness preservation to quantify the
                 differences in their fitness landscapes and to provide
                 guidance to researchers in determining which
                 problem/variation operator set is best for their
                 simulation.",
  keywords =     "genetic algorithms, genetic programming,
                 Smith-Waterman crossover, artificial genes, artificial
                 organisms, biological simulations, context free
                 grammar, gene interaction, genetic programming maximum
                 problem, genomic level, gridwalkers, horizontal gene
                 transfer, plus-one-recall-store, rugged multimodal
                 fitness landscapes, self-avoiding walk problem,
                 size-neutral crossover, variable length strings,
                 biology computing, context-free grammars, genetics",
  DOI =          "doi:10.1109/CIBCB.2011.5948463",
  notes =        "Also known as \cite{5948463}",
}

Genetic Programming entries for Wendy Ashlock Daniel Ashlock

Citations