• DocumentCode
    424019
  • Title

    An algorithm for finding reliably schedulable plans

  • Author

    Takács, Balint ; Szita, István ; Lorincz, András

  • Author_Institution
    Dept. of Inf. Syst., Eotvos Lorand Univ., Budapest, Hungary
  • Volume
    3
  • fYear
    2004
  • fDate
    25-29 July 2004
  • Firstpage
    2257
  • Abstract
    For interacting agents in time-critical applications, learning whether a subtask can be scheduled reliably is an important issue. The identification of sub-problems of this nature may promote e.g., planning, scheduling and segmenting in Markov decision processes. We define a subtask to be schedulable if its execution time has a small variance. We present an algorithm for finding such subtasks.
  • Keywords
    Markov processes; decision theory; learning (artificial intelligence); planning (artificial intelligence); scheduling; Markov decision processes; execution time scheduling; interacting agents; reliable scheduling plans; subproblems identification; time critical applications; Artificial intelligence; Cost function; Decision making; Information systems; Learning; Process planning; Scheduling algorithm; State-space methods; Stochastic processes; Time factors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-8359-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2004.1380973
  • Filename
    1380973