Evolving reliable and robust controllers for real robots by genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Wei-Po Lee and John Hallam",
  title =        "Evolving reliable and robust controllers for real
                 robots by genetic programming",
  journal =      "Soft Computing -- A Fusion of Foundations,
                 Methodologies and Applications",
  year =         "1999",
  volume =       "3",
  number =       "2",
  pages =        "63--75",
  month =        sep,
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1432-7643",
  DOI =          "doi:10.1007/s005000050054",
  abstract =     "Using Genetic Programming (GP)-based approaches to
                 evolve robot controllers has the advantage of operating
                 variable-size genotype. This is an important feature
                 for evolving robot control systems as it allows
                 complete freedom for the control architecture in
                 respect to the task complexity which is difficult to
                 predict. However, GP-based work in evolving controllers
                 has been questioned in the verification of the
                 performance on real robots, the generalisation of
                 defining primitives, and the computational cost needed.
                 In this paper, we present our GP framework in which a
                 special representation of the robot controller is
                 designed; this representation can capture well the
                 characteristic of a behaviour controller so that our
                 system can efficiently evolve desired robot behaviours
                 by a relatively low computational cost. This system has
                 been successfully used to evolve reliable and robust
                 controllers working on a real robot, for a variety of

Genetic Programming entries for Wei-Po Lee John Hallam