• DocumentCode
    2119930
  • Title

    Causal Graph Based Dynamic Optimization of Hierarchies for Factored MDPs

  • Author

    Hongbing Wang ; Jiancai Zhou ; Xuan Zhou

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Southeast Univ., Nanjing, China
  • Volume
    1
  • fYear
    2012
  • fDate
    4-7 Dec. 2012
  • Firstpage
    579
  • Lastpage
    582
  • Abstract
    This paper presents an approach based on casual graph to optimize the task hierarchies for Hierarchical Reinforcement Learning (HRL). We conducted experiments to show that the resulting task hierarchies can improve effectiveness of reinforcement leaning.
  • Keywords
    dynamic programming; graph theory; learning (artificial intelligence); HRL; causal graph based dynamic optimization; factored MDP; hierarchical reinforcement learning; task hierarchy; Complex systems; casual graph; genetic programming; hierarchical reinforcement learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology (WI-IAT), 2012 IEEE/WIC/ACM International Conferences on
  • Conference_Location
    Macau
  • Print_ISBN
    978-1-4673-6057-9
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2012.59
  • Filename
    6511944
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2119930