Introducing particle swarm optimization into a genetic algorithm to evolve robot controllers

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "Malte Langosz and Kai Alexander {von Szadkowski} and 
                 Frank Kirchner",
  title =        "Introducing particle swarm optimization into a genetic
                 algorithm to evolve robot controllers",
  booktitle =    "GECCO Comp '14: Proceedings of the 2014 conference
                 companion on Genetic and evolutionary computation
  year =         "2014",
  editor =       "Christian Igel and Dirk V. Arnold and 
                 Christian Gagne and Elena Popovici and Anne Auger and 
                 Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and 
                 Kalyanmoy Deb and Benjamin Doerr and James Foster and 
                 Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and 
                 Hitoshi Iba and Christian Jacob and Thomas Jansen and 
                 Yaochu Jin and Marouane Kessentini and 
                 Joshua D. Knowles and William B. Langdon and Pedro Larranaga and 
                 Sean Luke and Gabriel Luque and John A. W. McCall and 
                 Marco A. {Montes de Oca} and Alison Motsinger-Reif and 
                 Yew Soon Ong and Michael Palmer and 
                 Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and 
                 Guenther Ruhe and Tom Schaul and Thomas Schmickl and 
                 Bernhard Sendhoff and Kenneth O. Stanley and 
                 Thomas Stuetzle and Dirk Thierens and Julian Togelius and 
                 Carsten Witt and Christine Zarges",
  isbn13 =       "978-1-4503-2881-4",
  keywords =     "genetic algorithms, genetic programming, ant colony
                 optimization and swarm intelligence: Poster",
  pages =        "9--10",
  month =        "12-16 " # jul,
  organisation = "SIGEVO",
  address =      "Vancouver, BC, Canada",
  URL =          "",
  DOI =          "doi:10.1145/2598394.2598474",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "This paper presents Swarm-Assisted Behaviour Graph
                 Evolution (SABRE), a genetic algorithm which combines
                 elements from genetic programming and neuroevolution to
                 develop Behaviour Graphs (BGs). SABRE evolves graph
                 structure and parameters in parallel, with particle
                 swarm optimisation (PSO) being used for the latter. The
                 algorithm's performance was evaluated on a set of
                 black-box function approximation problems, one of which
                 represents part of a robot controller. We found that
                 SABRE performed significantly better in approximating
                 the mathematically complex test functions than the
                 reference algorithms genetic programming (GP) and
  notes =        "Also known as \cite{2598474} Distributed at

Genetic Programming entries for Malte Langosz Kai Alexander von Szadkowski Frank Kirchner