A Q-Learning Based Hyper-Heuristic for Generating Efficient UAV Swarming Behaviours

Reference : A Q-Learning Based Hyper-Heuristic for Generating Efficient UAV Swarming Behaviours


	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/10993/49055

Title :	A Q-Learning Based Hyper-Heuristic for Generating Efficient UAV Swarming Behaviours
Language :	English
Author, co-author :	Duflo, Gabriel [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > PCOG]
	Danoy, Grégoire [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)]
	Talbi, El-Ghazali [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)]
	Bouvry, Pascal [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)]
Publication date :	2021
Main document title :	Intelligent Information and Database Systems - 13th Asian Conference ACIIDS 2021, Phuket, Thailand, April 7-10, 2021, Proceedings
Publisher :	Springer
Collection and collection volume :	Lecture Notes in Computer Science
Pages :	768--781
Peer reviewed :	Yes
Audience :	International
Event name :	Asian Conference on Intelligent Information and Database Systems (ACIIDS)
Event date :	April 7–10 2021
Permalink :	http://hdl.handle.net/10993/49055
DOI :	10.1007/978-3-030-73280-6\_61
Other URL :	https://doi.org/10.1007/978-3-030-73280-6\_61

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