Evolution of learning rules for supervised tasks I: simple learning problems

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

@TechReport{Kuscu:1995:elrst1,
  author =       "Ibrahim Kuscu",
  title =        "Evolution of learning rules for supervised tasks I:
                 simple learning problems",
  institution =  "School of Cognitive and Computing Sciences, University
                 of Sussex",
  year =         "1995",
  type =         "Cognitive Science Research Paper",
  number =       "394",
  address =      "Falmer, Brighton, Sussex, UK",
  month =        "10 " # nov,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp394.ps.Z",
  abstract =     "Initial experiments with a genetic-based encoding
                 schema are presented as a potentially powerful tool to
                 discover learning rules by means of evolution. Several
                 simple supervised learning tasks are tested. The
                 results indicate the potential of the encoding schema
                 to discover learning rules for more complex and larger
                 learning problems.",
  size =         "18 pages",
}

Genetic Programming entries for Ibrahim Kuscu

Citations