Exploring and evolving process-oriented control for real and virtual fire fighting robots

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "Kathryn Hardey and Eren Corapcioglu and 
                 Molly Mattis and Mark Goadrich and Matthew Jadud",
  title =        "Exploring and evolving process-oriented control for
                 real and virtual fire fighting robots",
  booktitle =    "GECCO '12: Proceedings of the fourteenth international
                 conference on Genetic and evolutionary computation
  year =         "2012",
  editor =       "Terry Soule and Anne Auger and Jason Moore and 
                 David Pelta and Christine Solnon and Mike Preuss and 
                 Alan Dorin and Yew-Soon Ong and Christian Blum and 
                 Dario Landa Silva and Frank Neumann and Tina Yu and 
                 Aniko Ekart and Will Browne and Tim Kovacs and 
                 Man-Leung Wong and Clara Pizzuti and Jon Rowe and Tobias Friedrich and 
                 Giovanni Squillero and Nicolas Bredeche and 
                 Stephen L. Smith and Alison Motsinger-Reif and Jose Lozano and 
                 Martin Pelikan and Silja Meyer-Nienberg and 
                 Christian Igel and Greg Hornby and Rene Doursat and 
                 Steve Gustafson and Gustavo Olague and Shin Yoo and 
                 John Clark and Gabriela Ochoa and Gisele Pappa and 
                 Fernando Lobo and Daniel Tauritz and Jurgen Branke and 
                 Kalyanmoy Deb",
  isbn13 =       "978-1-4503-1177-9",
  pages =        "105--112",
  keywords =     "genetic algorithms, genetic programming, artificial
                 life/robotics/evolvable hardware",
  month =        "7-11 " # jul,
  organisation = "SIGEVO",
  address =      "Philadelphia, Pennsylvania, USA",
  DOI =          "doi:10.1145/2330163.2330179",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "Current research in evolutionary robotics is largely
                 focused on creating controllers by either evolving
                 neural networks or refining genetic programs based on
                 grammar trees. We propose the use of the parallel,
                 dataflow languages for the construction of effective
                 robotic controllers and the evolution of new
                 controllers using genetic programming techniques. These
                 languages have the advantages of being built on
                 concurrent execution frameworks that lend themselves to
                 formal verification along with being visualized as a
                 dataflow graph. In this paper, we compare and contrast
                 the development and subsequent evolution of one such
                 process-oriented control algorithm. Our control
                 software was built from composable, communicating
                 processes executing in parallel, and we tested our
                 solution in an annual fire-fighting robotics
                 competition. Subsequently, we evolved new controllers
                 in a virtual simulation of this parallel dataflow
                 domain, and in doing so discovered and quantified more
                 efficient solutions. This research demonstrates the
                 effectiveness of using process networks as the basis
                 for evolutionary robotics.",
  notes =        "Also known as \cite{2330179} GECCO-2012 A joint
                 meeting of the twenty first international conference on
                 genetic algorithms (ICGA-2012) and the seventeenth
                 annual genetic programming conference (GP-2012)",

Genetic Programming entries for Kathryn Hardey Eren Corapcioglu Molly Mattis Mark Goadrich Matthew Jadud