• DocumentCode
    1887114
  • Title

    Emergence of adaptive behavior by chaotic neural networks

  • Author

    Suzuki, Ikuo ; Yokoi, Hiroshi ; Kakazu, Yukinori

  • Author_Institution
    Graduate Sch. of Eng., Hokkaido Univ., Japan
  • Volume
    1
  • fYear
    2003
  • fDate
    16-20 July 2003
  • Firstpage
    151
  • Abstract
    In this paper, we propose an emergent system in which an autonomous mobile robot can acquire environment oriented behavior. In the general robotic engineering, a system designer gave the model of environment and sensory-motor commands beforehand. However, we think that the autonomous robot has to be developed through the interaction between robot´s behavior and the environmental information by itself. So, we construct the controller for the autonomous robot to acquire the adaptive behavior with the chaotic neural networks (CNNs). Furthermore, we make use of the dynamic learning method (DLM) as an on-line learning method. The results of the computational experiments show the chaotic search of this network plays an important role for the acquisition of the adaptive behavior.
  • Keywords
    adaptive systems; chaos; emergent phenomena; learning (artificial intelligence); mobile robots; neural nets; adaptive behavior emergence; autonomous mobile robot; chaotic neural networks; dynamic learning method; emergent system; environment oriented behavior; general robotic engineering; on-line learning method; sensory-motor commands; Adaptive control; Cellular neural networks; Chaos; Design engineering; Learning systems; Mobile robots; Neural networks; Programmable control; Robot sensing systems; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Robotics and Automation, 2003. Proceedings. 2003 IEEE International Symposium on
  • Print_ISBN
    0-7803-7866-0
  • Type

    conf

  • DOI
    10.1109/CIRA.2003.1222080
  • Filename
    1222080