Enhanced maritime situation awareness with negotiator agents

被引:0
|
作者
Hemaissia, Miniar
Seghrouchni, Amal El Fallah
Mattioli, Juliette
机构
[1] THALES Res & Technol France, PLATON Lab, F-91767 Palaiseau, France
[2] Univ Paris 06, Lab Informat Paris, CNRS, UMR 7606, F-75015 Paris, France
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
French coastguard missions have become increasingly varied implying new challenges such as the reduction of the decision cycle and the expansion of available information. Thus, it involves new needs for enhanced decision support. An efficient situation awareness system has to quickly detect and identify suspicious boats. The efficiency of such a system relies on a reliable sensor fusion since a coastguard uses sensors to achieve his mission. We present an innovative approach based on multi-agent negotiation to fuse classifiers, benefiting from the efficiency of existing classification tools and from the flexibility and reliability of a multi-agent system to exploit distributed data across dispersed sources. We developed a first prototype using a basic negotiation protocol in order to validate the feasibility and the interest of our approach. The results obtained are promising and encourage us to continue on this way.
引用
收藏
页码:14 / 23
页数:10
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