Co-evolutionary Approach to Design of Robotic Gait

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

@InProceedings{Cerny:evoapps13,
  author =       "Jan Cerny and Jiri Kubalik",
  title =        "Co-evolutionary Approach to Design of Robotic Gait",
  booktitle =    "Applications of Evolutionary Computing,
                 EvoApplications 2013: EvoCOMNET, EvoCOMPLEX, EvoENERGY,
                 EvoFIN, EvoGAMES, EvoIASP, EvoINDUSTRY, EvoNUM, EvoPAR,
                 EvoRISK, EvoROBOT, EvoSTOC",
  year =         "2013",
  month =        "3-5 " # apr,
  editor =       "Anna I. Esparcia-Alcazar and Antonio Della Cioppa and 
                 Ivanoe {De Falco} and Ernesto Tarantino and 
                 Carlos Cotta and Robert Schaefer and Konrad Diwold and 
                 Kyrre Glette and Andrea Tettamanzi and 
                 Alexandros Agapitos and Paolo Burrelli and J. J. Merelo and 
                 Stefano Cagnoni and Mengjie Zhang and Neil Urquhart and Kevin Sim and 
                 Aniko Ekart and Francisco {Fernandez de Vega} and 
                 Sara Silva and Evert Haasdijk and Gusz Eiben and 
                 Anabela Simoes and Philipp Rohlfshagen",
  series =       "LNCS",
  volume =       "7835",
  publisher =    "Springer Verlag",
  address =      "Vienna",
  publisher_address = "Berlin",
  pages =        "550--559",
  organisation = "EvoStar",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-37191-2",
  DOI =          "doi:10.1007/978-3-642-37192-9_55",
  size =         "10 pages",
  abstract =     "Manual design of motion patterns for legged robots is
                 difficult task often with suboptimal results. To
                 automate this process variety of approaches have been
                 tried including various evolutionary algorithms. In
                 this work we present an algorithm capable of generating
                 viable motion patterns for multi-legged robots. This
                 algorithm consists of two evolutionary algorithms
                 working in co-evolution. The GP is evolving motion of a
                 single leg while the GA deploys the motion to all legs
                 of the robot. Proof-of-concept experiments show that
                 the co-evolutionary approach delivers significantly
                 better results than those evolved for the same robot
                 with simple genetic programming algorithm alone.",
  notes =        "http://www.kevinsim.co.uk/evostar2013/cfpEvoApplications.html
                 EvoApplications2013 held in conjunction with
                 EuroGP2013, EvoCOP2013, EvoBio'2013 and EvoMusArt2013",
}

Genetic Programming entries for Jan Cerny Jiri Kubalik

Citations