• DocumentCode
    1599085
  • Title

    Cooperative behavior acquisition in multi-mobile robots environment by reinforcement learning based on state vector estimation

  • Author

    Uchibe, Eiji ; Asada, Minoru ; Hosoda, Koh

  • Author_Institution
    Graduate Sch. of Eng., Osaka Univ., Japan
  • Volume
    2
  • fYear
    1998
  • Firstpage
    1558
  • Abstract
    This paper proposes a method that acquires robots´ behaviors based on the estimation of the state vectors. In order to acquire the cooperative behaviors in multi-robot environments, each learning robot estimates the local predictive model between the learner and the other objects separately. Based on the local predictive models, the robots learn the desired behaviors using reinforcement learning. The proposed method is applied to a soccer playing situation, where a rolling ball and other moving robots are well modeled and the learner´s behaviors are successfully acquired by the method. Computer simulations and real experiments are shown and a discussion is given
  • Keywords
    cooperative systems; learning (artificial intelligence); mobile robots; predictive control; software agents; state estimation; behaviour based control; cooperative systems; multiple agents; multiple mobile robots; predictive models; reinforcement learning; state vector estimation; Adaptive systems; Artificial intelligence; High performance computing; Learning; Mobile robots; Neurons; Predictive models; Robot kinematics; Robot sensing systems; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 1998. Proceedings. 1998 IEEE International Conference on
  • Conference_Location
    Leuven
  • ISSN
    1050-4729
  • Print_ISBN
    0-7803-4300-X
  • Type

    conf

  • DOI
    10.1109/ROBOT.1998.677351
  • Filename
    677351