Evolving Controllers for Real Robots: A Survey of the Literature

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@Article{walker:2003:AB,
  author =       "Joanne Walker and Simon Garrett and Myra Wilson",
  title =        "Evolving Controllers for Real Robots: A Survey of the
                 Literature",
  journal =      "Adaptive Behavior",
  year =         "2003",
  volume =       "11",
  number =       "3",
  pages =        "179--203",
  month =        sep,
  keywords =     "genetic algorithms, genetic programming, evolutionary
                 robotics, physical robots, simulation, training,
                 lifelong adaptation by evolution, GA, EP",
  URL =          "http://users.aber.ac.uk/jnw/pubs/Walkeretal.pdf",
  DOI =          "doi:10.1177/1059712303113003",
  abstract =     "For many years, researchers in the field of mobile
                 robotics have been investigating the use of genetic and
                 evolutionary computation (GEC) to aid the development
                 of mobile robot controllers. Alongside the fundamental
                 choices of the GEC mechanism and its operators, which
                 apply to both simulated and physical evolutionary
                 robotics, other issues have emerged which are specific
                 to the application of GEC to physical mobile robotics.
                 This article presents a survey of recent methods in
                 GEC-developed mobile robot controllers, focusing on
                 those methods that include a physical robot at some
                 point in the learning loop. It simultaneously relates
                 each of these methods to a framework of two orthogonal
                 issues: the use of a simulated and/or a physical robot,
                 and the use of finite, training phase evolution prior
                 to a task and/or lifelong adaptation by evolution
                 during a task. A list of evaluation criteria are
                 presented and each of the surveyed methods are compared
                 to them. Analyses of the framework and evaluation
                 criteria suggest several possibilities; however, there
                 appear to be particular advantages in combining
                 simulated, training phase evolution (TPE) with lifelong
                 adaptation by evolution (LAE) on a physical robot.",
}

Genetic Programming entries for Joanne Walker Simon Garrett Myra Wilson

Citations