• DocumentCode
    3391744
  • Title

    A multi-agent approach to involve multiple knowledge models and the case base reasoning approach in decision support systems

  • Author

    Colloc, Joël ; Sybord, Christine

  • Author_Institution
    Univ. of Lyon 3, France
  • fYear
    2003
  • fDate
    16-18 March 2003
  • Firstpage
    247
  • Lastpage
    251
  • Abstract
    The building of Decision Support System (DSS) in complex domains like management, medicine, environment...requires to involve various data and knowledge models and to support the reasoning modes taking place in the professional cognitive process during his or her job practice. We propose a Multi-Agent Decision Support System (MADSS) architecture to integrate the different categories of knowledge representation. We describe the functionalities and capacities of cognitive agents implementing these different kinds of knowledge and bringing them to cooperate in elaborating the decision. Agents are able to commit to build sub-decisions and thus, the system provides a whole sequence of decisions fitting the user´s usual cognitive scheme. We trust in a supervised architecture because such a MADSS must be goal driven by the user´s requirements. However, the agents remain autonomous and keep the opportunity to commit or not to the task exhibited by the supervisor at the moment.
  • Keywords
    case-based reasoning; decision support systems; knowledge representation; multi-agent systems; software agents; Multi-Agent Decision Support System architecture; cognitive process; data models; decision support systems; knowledge models; knowledge representation; reasoning modes; supervised architecture; Buildings; Computer aided software engineering; Databases; Decision making; Decision support systems; Environmental management; Epilepsy; Knowledge based systems; Knowledge management; Medical diagnostic imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Theory, 2003. Proceedings of the 35th Southeastern Symposium on
  • ISSN
    0094-2898
  • Print_ISBN
    0-7803-7697-8
  • Type

    conf

  • DOI
    10.1109/SSST.2003.1194567
  • Filename
    1194567