• DocumentCode
    1593979
  • Title

    Influence networks: a reactive planning architecture

  • Author

    Tychonievich, Lou ; Smith, Thomas C. ; Evans, Robert

  • Author_Institution
    Martin Marietta Aero & Naval Syst., Baltimore, MD, USA
  • fYear
    1991
  • Firstpage
    354
  • Lastpage
    360
  • Abstract
    An architecture for reactive planning, called an influence network, is presented. Most approaches to planning involve goal decomposition, action generation, and action fusion, the latter being the most difficult. In an influence network, fusion involves influences, rather than fully specified actions. An influence serves to constrain or bias the eventual selection of actions. Plans to satisfy individual goals generate influences. These influences are validated as they are generated to ensure that they are consistent with influences already accepted. After all influences have been processed, actions are generated which satisfy the influences that have been accepted. Influence networks provide a simple method of action fusion by delaying commitment while not delaying validation. As a result, plan repair, can be accomplished by the individual planning agents as their plans are being constructed, rather than being performed at the system level
  • Keywords
    constraint theory; planning (artificial intelligence); action fusion; action selection; bias; constraints; delayed commitment; goal satisfaction; influence network; plan repair; planning agents; reactive planning architecture; validation, consistency; Command and control systems; Control systems; Delay; Diversity reception; Fusion power generation; Performance evaluation; Process planning; Prototypes; Real time systems; Underwater vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence Applications, 1991. Proceedings., Seventh IEEE Conference on
  • Conference_Location
    Miami Beach, FL
  • Print_ISBN
    0-8186-2135-4
  • Type

    conf

  • DOI
    10.1109/CAIA.1991.120892
  • Filename
    120892