• DocumentCode
    476266
  • Title

    Adaptive and cooperative learning for Robocup agents

  • Author

    Kuo, Jong Yih ; Hsieh, Frank

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Taipei Univ. of Technol., Taipei
  • Volume
    6
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    3125
  • Lastpage
    3131
  • Abstract
    In this paper, we study several adaptive learning strategies for robot agents in a Robocop game. A Q-learning based method is introduced to learning the mapping among agentpsilas actions. We apply these strategies to improve robotpsilas plan. In order to facilitate the development of shred understanding among game strategies, Pigetpsilas cognitive theory is applied to the use of cooperative learning. This paper uses a RoboCup game to explain our approach.
  • Keywords
    cognitive systems; cooperative systems; intelligent robots; learning systems; mobile robots; multi-robot systems; sport; Q-learning based method; Robocup agents; adaptive learning; cooperative learning; game strategies; mapping learning; robot agents; Cognition; Cognitive robotics; Computer science; Cybernetics; Intelligent agent; Intelligent robots; Machine learning; Process design; Robot sensing systems; Robotics and automation; Adaptive Learning; Cooperative Learning; Intelligent agent;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4620945
  • Filename
    4620945
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=476266