Optimizing the Performance of an Unpredictable UAV Swarm for Intruder Detection

Reference : Optimizing the Performance of an Unpredictable UAV Swarm for Intruder Detection


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/44002

Title :	Optimizing the Performance of an Unpredictable UAV Swarm for Intruder Detection
Language :	English
Author, co-author :	Stolfi Rosso, Daniel [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Brust, Matthias R. [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) >]
	Danoy, Grégoire [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Computer Science and Communications Research Unit (CSC)]
	Bouvry, Pascal [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)]
Publication date :	2020
Main document title :	Optimization and Learning - Third International Conference, OLA 2020, Cádiz, Spain, February 17-19, 2020, Proceedings
Publisher :	Springer
Collection and collection volume :	Communications in Computer and Information Science
Pages :	37--48
Peer reviewed :	Yes
On invitation :	No
Audience :	International
Event name :	Third International Conference on Optimization and Learning (OLA 2020)
Event date :	17-02-2020
Permalink :	http://hdl.handle.net/10993/44002
DOI :	10.1007/978-3-030-41913-4_4
Other URL :	https://doi.org/10.1007/978-3-030-41913-4_4
Commentary :	1173

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