Evolution of a subsumption architecture that performs a wall following task for an autonomous mobile robot via genetic programming

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

@InCollection{Koza:1994:wallGP,
  author =       "John R. Koza",
  title =        "Evolution of a subsumption architecture that performs
                 a wall following task for an autonomous mobile robot
                 via genetic programming",
  booktitle =    "Computational Learning Theory and Natural Learning
                 Systems",
  publisher =    "MIT Press",
  year =         "1994",
  editor =       "Stephen Jose Hanson and Thomas Petsche and 
                 Ronald L. Rivest and Michael Kearns",
  volume =       "2",
  pages =        "321--346",
  address =      "Cambridge, MA, USA",
  month =        jun,
  ISBN =         "0-262-58133-7",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.genetic-programming.com/jkpdf/cltnls1994.pdf",
  abstract =     "The goal in automatic programming is to get a computer
                 to perform a task by telling it what needs to be done,
                 rather than by explicitly programming it. This paper
                 considers the task of automatically generating a
                 computer program to enable an autonomous mobile robot
                 to perform the task of following the wall of an
                 irregular shaped room. A human programmer has written
                 such a program in the style of the subsumption
                 architecture. The solution produced by genetic
                 programming emerges as a result of Darwinian natural
                 selection and genetic crossover (sexual recombination)
                 in a population of computer programs. This evolutionary
                 process is driven by a fitness measure which
                 communicates the nature of the task to the computer.",
}

Genetic Programming entries for John Koza

Citations