• DocumentCode
    404240
  • Title

    Learning, optimizing, and distributed decision making based on experience

  • Author

    Ho, Yu-Chi

  • Author_Institution
    Harvard Univ., Cambridge, MA, USA
  • Volume
    5
  • fYear
    2003
  • fDate
    9-12 Dec. 2003
  • Firstpage
    4818
  • Abstract
    We present a short and simplified "derivation" and discussion of perturbation analysis (PA), Markov decision problems (MDP), and reinforcement learning (RL) based on the sample path approach.
  • Keywords
    Markov processes; distributed decision making; learning (artificial intelligence); optimisation; perturbation techniques; Markov decision problems; distributed decision making; experience; optimization; perturbation analysis; reinforcement learning; sample path method; Contracts; Convergence; Costs; Distributed decision making; Dynamic programming; History; Learning; Stability analysis; State-space methods; Steady-state;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-7924-1
  • Type

    conf

  • DOI
    10.1109/CDC.2003.1272352
  • Filename
    1272352
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=404240