• DocumentCode
    3196847
  • Title

    Reinforcement Learning for Routing in Ad Hoc Networks

  • Author

    Nurmi, Petteri

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Helsinki, Helsinki
  • fYear
    2007
  • fDate
    16-20 April 2007
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    We show how routing in ad hoc networks can be modeled as a sequential decision making problem with incomplete information. More precisely, we show how to map routing into a reinforcement learning problem involving a partially observable Markov decision process, and present an algorithm for optimizing the performance of the nodes in this model. We also present simulation results with our model.
  • Keywords
    ad hoc networks; learning (artificial intelligence); telecommunication computing; telecommunication network routing; Markov decision process; ad hoc networks routing; reinforcement learning; sequential decision making problem; Ad hoc networks; Communication networks; Costs; Function approximation; Game theory; Learning; Parameter estimation; Routing; Stochastic processes; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks and Workshops, 2007. WiOpt 2007. 5th International Symposium on
  • Conference_Location
    Limassol
  • Print_ISBN
    978-1-4244-0960-0
  • Electronic_ISBN
    978-1-4244-0961-7
  • Type

    conf

  • DOI
    10.1109/WIOPT.2007.4480049
  • Filename
    4480049
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3196847