Evolution of a world model for a miniature robot using genetic programming

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

  author =       "Peter Nordin and Wolfgang Banzhaf and 
                 Markus Brameier",
  title =        "Evolution of a world model for a miniature robot using
                 genetic programming",
  journal =      "Robotics and Autonomous Systems",
  volume =       "25",
  pages =        "105--116",
  year =         "1998",
  number =       "1-2",
  month =        "31 " # oct,
  keywords =     "genetic algorithms, genetic programming, Evolutionary
                 robotics, World model, On-line learning, Planning",
  ISSN =         "0921-8890",
  DOI =          "doi:10.1016/S0921-8890(98)00004-9",
  URL =          "http://citeseer.ist.psu.edu/cache/papers/cs/598/http:zSzzSzls11-www.informatik.uni-dortmund.dezSzpeoplezSzbanzhafzSzrobot32.pdf/nordin98evolution.pdf",
  URL =          "http://citeseer.ist.psu.edu/nordin98evolution.html",
  URL =          "http://www.sciencedirect.com/science/article/B6V16-3VSPF6D-7/1/883b0d9e78af0fc4f70e997adb715e89",
  abstract =     "We have used an automatic programming method called
                 genetic programming (GP) for control of a miniature
                 robot. Our earlier work on real-time learning suffered
                 from the drawback of the learning time being limited by
                 the response dynamics of the robot's environment. In
                 order to overcome this problem we have devised a new
                 technique which allows learning from past experiences
                 that are stored in memory. The new method shows its
                 advantage when perfect behavior emerges in experiments
                 quickly and reliably. It is tested on two control
                 tasks, obstacle avoiding and wall following behavior,
                 both in simulation and on the real robot platform

Genetic Programming entries for Peter Nordin Wolfgang Banzhaf Markus Brameier