• DocumentCode
    1551778
  • Title

    The influence model

  • Author

    Asavathiratham, Chalee ; Roy, Sandip ; Lesieutre, Bernard ; Verghese, George

  • Author_Institution
    McKinsey & Co., London, UK
  • Volume
    21
  • Issue
    6
  • fYear
    2001
  • fDate
    12/1/2001 12:00:00 AM
  • Firstpage
    52
  • Lastpage
    64
  • Abstract
    This article describes what we have termed the influence model, constructed to represent in a tractable way the dynamics of networked and interacting Markov chains. The constraints imposed on the influence model may restrict its modeling ability but permit explicit and detailed analysis and computation and still leave room for rather richly structured and novel behavior. We focus on the dynamic evolution of the system. The influence matrix H, in both the homogeneous and general cases, bears further study as an interesting generalization of familiar stochastic matrices. The influence model may also find use as a representation for stochastic signals of various kinds. The influence model is evidently related to other models of networked stochastic automata in the literature, but the details of the relationships remain to be worked out more explicitly in many cases. The generalizations embodied in the influence model could prove to be important degrees of freedom in particular applications
  • Keywords
    Markov processes; cellular automata; large-scale systems; matrix algebra; probability; reduced order systems; Markov chains; cellular automata; influence model; matrix algebra; probability; Communication networks; Context modeling; Humans; Mathematical model; Power engineering and energy; Power grids; Power system modeling; Power transmission lines; Stochastic processes; Uncertainty;
  • fLanguage
    English
  • Journal_Title
    Control Systems, IEEE
  • Publisher
    ieee
  • ISSN
    1066-033X
  • Type

    jour

  • DOI
    10.1109/37.969135
  • Filename
    969135