• DocumentCode
    1680081
  • Title

    Learning in traffic control: adaptive processes and EAMs

  • Author

    Selfridge, Oliver G. ; Feurzeig, Wally

  • Volume
    3
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    2598
  • Lastpage
    2603
  • Abstract
    The fundamentals of our approach are that every action undertaken by a (sub)agent is an act of control; and hence is contained in an adaptive loop. We present a number of elementary adaptive modules (EAMs), the basic building blocks of adaptive agent systems, with a discussion of their use, their control, and their behaviors under different conditions; we also discuss the host of problems that we expect to run into. We apply these ideas to a model of traffic control by agents that run vehicles and control traffic lights
  • Keywords
    adaptive control; adaptive systems; intelligent control; learning systems; multi-agent systems; road vehicles; traffic control; adaptive agent systems; adaptive loop; adaptive processes; elementary adaptive modules; traffic control; traffic lights; Adaptive control; Adaptive systems; Algorithms; Artificial intelligence; Control systems; Humans; Intelligent agent; Machine learning; Programmable control; Traffic control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7278-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2002.1007553
  • Filename
    1007553