• DocumentCode
    416899
  • Title

    Fuzzy target acquired by reinforcement learning for parking control

  • Author

    Yasunobu, Seiji ; Matsubara, Tomoya

  • Author_Institution
    Inst. of Eng. Mech. & Syst., Tsukuba Univ., Ibaraki, Japan
  • Volume
    2
  • fYear
    2003
  • fDate
    4-6 Aug. 2003
  • Firstpage
    1242
  • Abstract
    In this paper, a flexible action deciding method under various situations like a human being based on the concept of "fuzzy target" is proposed, and it applied to parking control. The "fuzzy target" is acquired by reinforcement learning, and it contains the grade of value of various targets. Fuzzy target is applied to intelligent parking control system for nonholonomic vehicle. The simulation results show the effectiveness of the proposed method.
  • Keywords
    digital simulation; fuzzy control; intelligent control; knowledge acquisition; learning (artificial intelligence); predictive control; traffic control; vehicles; digital simulation; flexible action deciding method; fuzzy target; intelligent parking control; knowledge acquisition; nonholonomic vehicle; predictive control; reinforcement learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE 2003 Annual Conference
  • Conference_Location
    Fukui, Japan
  • Print_ISBN
    0-7803-8352-4
  • Type

    conf

  • Filename
    1324142