• DocumentCode
    2307106
  • Title

    Towards imitation-enhanced Reinforcement Learning in multi-agent systems

  • Author

    Erbas, Mehmet D. ; Winfield, Alan F T ; Bull, Larry

  • Author_Institution
    Bristol Robot. Lab., Univ. of the West of England, Bristol, UK
  • fYear
    2011
  • fDate
    11-15 April 2011
  • Firstpage
    6
  • Lastpage
    13
  • Abstract
    Imitation, in which an individual observes and copies another´s actions, is a powerful means of learning. This paper presents a way of using imitation to enhance the learning capability of individual agents. The agents employ Q-learning and we show that agents with imitation enhanced Q-learning learn faster than those with Q-learning alone.
  • Keywords
    learning (artificial intelligence); multi-agent systems; Q-learning; imitation-enhanced reinforcement learning; multi-agent systems; Actuators; Adaptation models; Electronic mail; Greedy algorithms; Learning; Robots; Watches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Life (ALIFE), 2011 IEEE Symposium on
  • Conference_Location
    Paris
  • ISSN
    2160-6374
  • Print_ISBN
    978-1-61284-062-8
  • Type

    conf

  • DOI
    10.1109/ALIFE.2011.5954652
  • Filename
    5954652
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2307106