Cooperative body-brain coevolutionary synthesis of mechatronic systems

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@Article{DBLP:journals/aiedam/WangFTG08,
  author =       "Jiachuan Wang and Zhun Fan and Janis P. Terpenny and 
                 Erik D. Goodman",
  title =        "Cooperative body-brain coevolutionary synthesis of
                 mechatronic systems",
  journal =      "Artificial Intelligence for Engineering Design,
                 Analysis and Manufacturing",
  volume =       "22",
  number =       "3",
  year =         "2008",
  pages =        "219--234",
  doi =          "doi:10.1017/S0890060408000152",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  keywords =     "genetic algorithms, genetic programming, Bond Graphs,
                 Cooperative Coevolutionary Synthesis, Mechatronics",
  size =         "16 pages",
  abstract =     "To support the concurrent design processes of
                 mechatronic subsystems, unified mechatronics modeling
                 and cooperative body-brain coevolutionary synthesis are
                 developed. In this paper, both body-passive physical
                 systems and brain-active control systems can be
                 represented using the bond graph paradigm. Bond graphs
                 are combined with genetic programming to evolve
                 low-level building blocks into systems with high-level
                 functionalities including both topological
                 configurations and parameter settings. Design spaces of
                 coadapted mechatronic subsystems are automatically
                 explored in parallel for overall design optimality. A
                 quarter-car suspension system case study is provided.
                 Compared with conventional design methods, semiactive
                 suspension designs with more creativity and flexibility
                 are achieved through this approach.",
  notes =        "coevolution, Open Beagle",
}

Genetic Programming entries for Jiachuan Wang Zhun Fan Janis P Terpenny Erik Goodman