• DocumentCode
    2124551
  • Title

    A Three-Layer Cooperative Knowledge Modeling of Multi-agent Conflict System Based on Healthcare Sensor Decision Network

  • Author

    Dai, Zhifeng ; Sun, Baolin ; Wang, Hong ; Li, Yuanxiang

  • Author_Institution
    Sch. of Comput., Hubei Univ. of Econ., Wuhan
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    157
  • Lastpage
    160
  • Abstract
    With the promising practical application of WSN in EHS, this paper addresses itself to the interesting problem on uncertainty management up to knowledge modeling of healthcare sensor data. Enlightening ourselves on the inherently distributed as well as intelligent characteristic in common among WSN, MAS and RST, we propose a hybrid and multi-agent framework HSDN and the corresponding solution to three-layer cooperative knowledge modeling HSDN-MAHCKM, which result in gaining much informative insight into the inconsistent healthcare knowledge of multi-agent conflict system. And as expected, the tutorial conflict analysis of HSDN-MAHCKM based upon decision network, which provides a more quantitative rather than qualitative treatment of uncertainty in decisions, can deal with the real scenario with some noises and endow the various information processing agents with the capability to learn how to choose the most appropriate coordination strategy.
  • Keywords
    health care; multi-agent systems; cooperative knowledge modeling; healthcare sensor decision network; multiagent conflict system; tutorial conflict analysis; Information analysis; Information processing; Intelligent sensors; Medical services; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Sensor systems and applications; Uncertainty; Wireless sensor networks; cooperative knowledge modeling; healthcare sensor decision network; multi-agent conflict system; rough set; uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3488-6
  • Type

    conf

  • DOI
    10.1109/KAM.2008.178
  • Filename
    4732806