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Huiting Wang, Yazhi Liu, Wei Li and Zhigang Yang
In data center networks, when facing challenges such as traffic volatility, low resource utilization, and the difficulty of a single traffic scheduling strategy to meet demands, it is necessary to introduce intelligent traffic scheduling mechanisms to im...
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P.V. Kumaraguru, Vidyavathi Kamalakkannan, Gururaj H L, Francesco Flammini, Badria Sulaiman Alfurhood and Rajesh Natarajan
Terabytes of data are now being handled by an increasing number of apps, and rapid user decision-making is hampered by data analysis. At the same time, there is a rise in interest in big data analysis for social networks at the moment. Thus, adopting dis...
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Lei Wang, Guanwen Chen, Tai Li and Ruitian Yang
In this study, wireless sensor networks and time base generators are used to solve the fixed-time containment control problem in multi-agent systems with fixed topologies. A new event-triggered control protocol is proposed, which combines a fully distrib...
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Shaowei Li, Yongchao Wang, Yaoming Zhou, Yuhong Jia, Hanyue Shi, Fan Yang and Chaoyue Zhang
Multiple unmanned aerial vehicle (multi-UAV) cooperative air combat, which is an important form of future air combat, has high requirements for the autonomy and cooperation of unmanned aerial vehicles. Therefore, it is of great significance to study the ...
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Shao Xuan Seah and Sutthiphong Srigrarom
This paper explores the use of deep reinforcement learning in solving the multi-agent aircraft traffic planning (individual paths) and collision avoidance problem for a multiple UAS, such as that for a cargo drone network. Specifically, the Deep Q-Networ...
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Naifeng Wen, Yundong Long, Rubo Zhang, Guanqun Liu, Wenjie Wan and Dian Jiao
This research introduces a two-stage deep reinforcement learning approach for the cooperative path planning of unmanned surface vehicles (USVs). The method is designed to address cooperative collision-avoidance path planning while adhering to the Interna...
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Juan Carlos Oliveros and Hashem Ashrafiuon
The trajectory planning and control of multi-agent systems requires accurate localization, which may not be possible when GPS signals and fixed features required for SLAM are not available. Cooperative Localization (CL) in multi-agent systems offers a sh...
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Jonathan Ponniah and Or D. Dantsker
A system is considered in which agents (UAVs) must cooperatively discover interest-points (i.e., burning trees, geographical features) evolving over a grid. The objective is to locate as many interest-points as possible in the shortest possible time fram...
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Sergi Mas-Pujol, Esther Salamí and Enric Pastor
Air traffic flow management (ATFM) is of crucial importance to the European Air Traffic Control System due to two factors: first, the impact of ATFM, including safety implications on ATC operations; second, the possible consequences of ATFM measures on b...
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Sisay Tadesse Arzo, Zeinab Akhavan, Mona Esmaeili, Michael Devetsikiotis and Fabrizio Granelli
Recently, a multi-agent based network automation architecture has been proposed. The architecture is named multi-agent based network automation of the network management system (MANA-NMS). The architectural framework introduced atomized network functions...
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