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
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