Investigation on Evolutionary Synthesis of Movement Commands

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

@Article{Oplatkova:2009:MSE,
  author =       "Zuzana Oplatkova and Ivan Zelinka",
  title =        "Investigation on Evolutionary Synthesis of Movement
                 Commands",
  journal =      "Modelling and Simulation in Engineering",
  year =         "2009",
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "16875591",
  URL =          "http://downloads.hindawi.com/journals/mse/2009/845080.pdf",
  DOI =          "doi:10.1155/2009/845080",
  bibsource =    "OAI-PMH server at www.doaj.org",
  language =     "eng",
  oai =          "oai:doaj-articles:3407db6981a4f0793fa9cea5d37ff9a1",
  broken =       "http://www.doaj.org/doaj?func=openurl\&genre=article\&issn=16875591\&date=2009\&volume=2009\&issue=\&spage=",
  publisher =    "Hindawi Publishing Corporation",
  abstract =     "This paper deals with usage of an alternative tool for
                 symbolic regression---analytic programming which is
                 able to solve various problems from the symbolic
                 domain, as well as genetic programming and grammatical
                 evolution. This paper describes a setting of an optimal
                 trajectory for a robot (originally designed as an
                 artificial ant on Santa Fe trail) solved by means of
                 analytic programming. Firstly, main principles of
                 analytic programming are described and explained. The
                 second part shows how analytic programming was used for
                 the application of finding a suitable trajectory step
                 by step. Because analytic programming needs
                 evolutionary algorithms for its run, three evolutionary
                 algorithms were used---self-organizing migrating
                 algorithm, differential evolution, and simulated
                 annealing---to show that anyone can be used. The total
                 number of simulations was 150 and results show that the
                 first two used algorithms were more successful than not
                 so robust simulated annealing.",
  notes =        "Article ID 845080

                 Faculty of Applied Informatics, Tomas Bata University
                 in Zlin, Nad Stranemi 4511, 762 72 Zlin, Czech
                 Republic",
}

Genetic Programming entries for Zuzana Oplatkova Ivan Zelinka

Citations