Crossover context in page-based linear genetic programming

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

  author =       "Garnett Wilson and Malcolm Heywood",
  title =        "Crossover context in page-based linear genetic
  journal =      "Canadian Journal of Electrical and Computer
  year =         "2002",
  volume =       "27",
  number =       "3",
  pages =        "113--116",
  organisation = "IEEE Canada",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, strategy
  ISSN =         "0840-8688",
  broken =       "",
  abstract =     "This work explores strategy learning through genetic
                 programming in artificial 'ants' that navigate the San
                 Mateo trail. We investigate several properties of
                 linearly structured (as opposed to typical tree-based)
                 GP including: the significance of simple register based
                 memories, the significance of constraints applied to
                 the crossover operator, and how 'active' the ant are.
                 We also provide a basis for investigating more
                 thoroughly the relation between specific code sequences
                 and fitness by dividing the genome into pages of
                 instructions and introducing an analysis of fitness
                 change and exploration of the trail done by particular
                 parts of a genome. By doing so we are able to present
                 results on how best to find the instructions in an
                 individual's program that contribute positively to the
                 accumulation of effective search strategies.",
  notes =        "Author says same content as \cite{wilson:2003:ccpb}",

Genetic Programming entries for Garnett Carl Wilson Malcolm Heywood