LSTM Path-Maker: a new LSTM-based strategy for the multi-agent patrolling

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dc.contributor.author Othmani-Guibourg, Mehdi
dc.contributor.author Farges, Jean-Loup
dc.contributor.author El Fallah Seghrouchni, Amal
dc.date.accessioned 2019-01-02T23:43:37Z
dc.date.available 2019-01-02T23:43:37Z
dc.date.issued 2019-01-08
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2019.076
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/59502
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Emerging Issues in Distributed Group Decision-Making: Opportunities and Challenges
dc.subject Collaboration Systems and Technologies
dc.subject Artificial Neural Networks, Long Short-Term Memory, Multi-agent Coordinating, Multi-agent patrolling, Multi-agent systems
dc.title LSTM Path-Maker: a new LSTM-based strategy for the multi-agent patrolling
dc.type Conference Paper
dc.type.dcmi Text
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Emerging Issues in Distributed Group Decision-Making: Opportunities and Challenges