• DocumentCode
    2734586
  • Title

    Applying Metareasoning to Swarming Systems: Approaches and Architectures

  • Author

    Brueckner, Sven A. ; Parunak, H.V.D.

  • Author_Institution
    Vector Res. Center, TechTeam Gov. Solutions, Inc., Ann Arbor, MI, USA
  • fYear
    2010
  • fDate
    27-28 Sept. 2010
  • Firstpage
    317
  • Lastpage
    322
  • Abstract
    Metareasoning is defined as the application of reasoning techniques to the process of reasoning itself. As such, it is not immediately concerned with the particular domain of an application, but with the decision processes and knowledge representations that provide the application functionality. A primary reason to perform metareasoning is the desire to reflect on the application´s performance and adapt its reasoning processes when needed. Research in metareasoning typically assumes that the domain reasoning is performed by a single process with symbolic knowledge representations and that both the process and the knowledge are accessible to the metareasoning component. Self-organizing systems with emergent properties stand in stark contrast to this assumed architecture. There, the application function is not explicitly encoded into a single entity but it emerges dynamically from complex interactions of simple agents. In this position paper we discuss the challenge of metareasoning in swarming systems and present three examples from past work that suggest possible approaches.
  • Keywords
    inference mechanisms; knowledge representation; multi-agent systems; self-adjusting systems; decision process; domain reasoning; metareasoning; reasoning technique; self-organizing systems; swarming system; symbolic knowledge representation; Adaptation model; Analytical models; Avatars; Cognition; Conferences; Monitoring; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Self-Adaptive and Self-Organizing Systems Workshop (SASOW), 2010 Fourth IEEE International Conference on
  • Conference_Location
    Budapest
  • Print_ISBN
    978-1-4244-8684-7
  • Type

    conf

  • DOI
    10.1109/SASOW.2010.64
  • Filename
    5729642