• DocumentCode
    2414946
  • Title

    Qualitative reinforcement learning control

  • Author

    Franklin, Judy A.

  • Author_Institution
    GTE Lab. Inc., Waltham, MA, USA
  • fYear
    1992
  • fDate
    1992
  • Firstpage
    870
  • Abstract
    An attempt is made to develop a reinforcement learning controller for a system described in more abstract or behavioral terms than those addressed by most controllers. The learning experiments center on the behavior of a ball rolling on a track. The evolution is from prediction to control of the behavior. An attempt is also made to evaluate the experiments in order to think about learning and experimentation at higher levels. The abstract description in the ball system considered is provided by a qualitative behavior of the system, given certain state information and given certain knowledge. The knowledge used is described, and the necessity of solving the problem is explained. The knowledge description is cast as part of a hierarchical controller, and generalizations to higher forms of learning are proposed
  • Keywords
    adaptive control; hierarchical systems; learning systems; hierarchical controller; knowledge description; qualitative reinforcement learning control; rolling ball; Artificial neural networks; Control systems; Joining processes; Laboratories; Learning; Linear feedback control systems; Optimal control; Pi control; Proportional control; Robust stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1992., Proceedings of the 31st IEEE Conference on
  • Conference_Location
    Tucson, AZ
  • Print_ISBN
    0-7803-0872-7
  • Type

    conf

  • DOI
    10.1109/CDC.1992.371601
  • Filename
    371601