• DocumentCode
    3181847
  • Title

    Efficient Organization of Network Topology based on Reinforcement Signals

  • Author

    Kim, Chyon Hae ; Sugano, Shigeki ; Ogata, Tetsuya

  • Author_Institution
    Dept. of Mech. Eng., Waseda Univ., Tokyo
  • fYear
    2006
  • fDate
    9-15 Oct. 2006
  • Firstpage
    3154
  • Lastpage
    3159
  • Abstract
    We developed a learning system for autonomous robots that allows for autonomous exploration of the effective output, and has simple external parameters and a low calculation cost. We propose the concept of self-organizing network elements (SONE) for creating learning systems with these characteristics. We created and evaluated a self-organizing logic circuit by using this concept. Our results indicated this learning system had the characteristics
  • Keywords
    learning systems; neurocontrollers; robots; autonomous exploration; autonomous robots; learning system; network topology; reinforcement signals; self-organizing logic circuit; self-organizing network elements; Costs; Genetic algorithms; Intelligent robots; Learning systems; Logic circuits; Network topology; Neural networks; Orbital robotics; Robot control; Self-organizing networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    1-4244-0258-1
  • Electronic_ISBN
    1-4244-0259-X
  • Type

    conf

  • DOI
    10.1109/IROS.2006.282338
  • Filename
    4058881