• DocumentCode
    2339322
  • Title

    Why topological maps are useful for learning in an autonomous agent

  • Author

    Zrehen, Stephane ; Gaussier, Philippe

  • Author_Institution
    Microcomput. Lab., Swiss Federal Inst. of Technol., Lausanne, Switzerland
  • fYear
    1994
  • fDate
    7-9 Sept. 1994
  • Firstpage
    230
  • Lastpage
    241
  • Abstract
    We discuss the usefulness of topology presentation in an online learning neural control system. We discuss biological and information processing arguments. Then, we propose an experiment performed on a mobile robot that shows that with a probabilistic topological map (PTM) much less information needs to be learned than using a Winner Take All.
  • Keywords
    learning (artificial intelligence); mobile robots; neurocontrollers; probability; PTM; autonomous agent; information processing arguments; mobile robot; online learning neural control system; probabilistic topological map; topology presentation; Autonomous agents; Cognition; Control systems; Gaussian processes; Humans; Laboratories; Mobile robots; Network topology; Neural networks; Psychology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    From Perception to Action Conference, 1994., Proceedings
  • Print_ISBN
    0-8186-6482-7
  • Type

    conf

  • DOI
    10.1109/FPA.1994.636107
  • Filename
    636107