• DocumentCode
    3180342
  • Title

    Research on cooperation and learning in multi-agent system

  • Author

    Zheng, Shuli ; Luo, Xiangfeng ; Luo, Zhenghu ; Yang, Jingan ; Jingan Yang

  • Author_Institution
    Inst. of Artificial Intelligence, Hefei Univ. of Technol., China
  • Volume
    2
  • fYear
    2002
  • fDate
    26-30 Aug. 2002
  • Firstpage
    1159
  • Abstract
    Cooperation and learning in multi-agent systems (MAS) is of special interest in DAI. This paper presents a cooperation model called MACM that provides a flexible coordination mechanism to support cooperation and learning in MAS. The learning agent adopts model-free distributed Q-learning. By using projection method, the distributed Q-learning algorithm needs less storage space for the Q-table than the classical Q-learning.
  • Keywords
    distributed algorithms; learning (artificial intelligence); multi-agent systems; DAI; MACM; MAS; Q-table; cooperation; distributed Q-learning algorithm; distributed artificial intelligence; flexible coordination mechanism; learning; model-free distributed Q-learning; multi-agent system; reinforcement learning; Artificial intelligence; Bayesian methods; Centralized control; Computer aided instruction; Control systems; Councils; Game theory; Intelligent agent; Learning; Multiagent systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2002 6th International Conference on
  • Print_ISBN
    0-7803-7488-6
  • Type

    conf

  • DOI
    10.1109/ICOSP.2002.1179995
  • Filename
    1179995