MAS4AT, a self-adaptive MAS for alert triggering in maritime surveillance

被引：1
作者：
MAS4AT, un SMA auto-adaptatif pour le déclenchement d'alertes dans le cadre de la surveillance maritime
机构：
[1] Equipe SMAC, IRIT, Université de Toulouse, F-31062 Toulouse cedex
[2] UPETEC, F-31520 Ramonville Saint-Agne, Parc technologique du Canal
来源：
| 1600年 / Lavoisier卷 / 27期
关键词：
Alert triggering; I2C; Learning; Maritime surveillance; MAS4AT; Self-adaptive MAS;
D O I：
10.3166/RIA.27.371-395
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper introduces MAS4AT, a cooperative and self-adaptive multi-agent system for abnormal behaviour detection and alert triggering in maritime surveillance. MAS4AT is designed and implemented in the context of the I2C project, a FP7 European project in which we are involved, which aims at implementing a new generation of maritime surveillance system able to permanently track and monitor all type of ship tracks in vulnerable trading lanes in order (i) to detect abnormal ships behaviours, (ii) to analyse it and, (iii) to trigger alerts if these behaviours correspond to threatening situations. This paper presents I2C and then focuses on MAS4AT and its learning abilities by reinforcements. © 2013 Lavoisier.
引用
收藏
页码：371 / 395
页数：24
相关论文
共 37 条
[1]  
Andrade M.A., Chacon P., Merelo J.J., Moran F., Evaluation of secondary structure of proteins from UV circular dichroism spectra using an unsupervised learning neural network, Protein Engineering, 6, 4, pp. 383-390, (1993)
[2]  
Auslander B., Gupta K.M., Aha D.W., A comparative evaluation of anomaly detection algorithms for maritime video surveillance, Society of Photo-Optical Instrumentation Engineers, 8019, (2011)
[3]  
Barlow H.B., Unsupervised learning, Neural Computation, 1, 3, pp. 295-311, (1989)
[4]  
Capera D., George J.P., Gleizes M.P., Glize P., The AMAS theory for complex problem solving based on self-organizing cooperative agents, Enabling Technologies Infrastrucure for Collaborative Enterprises, pp. 383-388, (2003)
[5]  
Celik M., Dadaser-Celik F., Dokuz A.S., Anomaly detection in temperature data usinf DBSCAN algorithm, IEEE Innovations in Intelligent Systems and Applications (INISTA), pp. 91-95, (2011)
[6]  
Cohen C.J., Morelli F., Scott K.A., A surveillance system for the recognition of intent within individuals and crowds, Technologies for Homeland Security, 2008 IEEE Conference on, pp. 559-565, (2008)
[7]  
Coulom R., Reinforcement Learning Using Neural Networks, with Applications to Motor Control, (2002)
[8]  
Cram D., Découverte Interactive et Complète de Chroniques: Application À la Coconstruction de Connaissance À Partir de Traces, (2010)
[9]  
Description of Work, (2010)
[10]  
Dousson C., Suivi d'Évolution et Reconnaissance de Chroniques, (1994)
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