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Xin Liao and Khoi D. Hoang
Distributed Constraint Optimization Problems (DCOPs) are an efficient framework widely used in multi-agent collaborative modeling. The traditional DCOP framework assumes that variables are discrete and constraint utilities are represented in tabular form...
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Mukhtar Fatihu Hamza
Due to increased complexity and interactions between various subsystems, higher-order MIMO systems present difficulties in terms of stability and control performance. This study effort provides a novel, all-encompassing method for creating a decentralize...
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Yuzhu Zhang and Hao Xu
This study investigates the problem of decentralized dynamic resource allocation optimization for ad-hoc network communication with the support of reconfigurable intelligent surfaces (RIS), leveraging a reinforcement learning framework. In the present co...
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Muhammad Sher Ramzan, Anees Asghar, Ata Ullah, Fawaz Alsolami and Iftikhar Ahmad
The Internet of Things (IoT) consists of complex and dynamically aggregated elements or smart entities that need decentralized supervision for data exchanging throughout different networks. The artificial bee colony (ABC) is utilized in optimization prob...
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Jingtong Dai and Zheng Wang
This paper focuses on the dynamic economic emission dispatch (DEED) problem, to coordinate the distributed energy resources (DERs) in a power system and achieve economical and environmental operation. Distributed energy storages (ESs) are introduced into...
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Kirill Chernov, Uliana Monakhova, Yaroslav Mashtakov, Shamil Biktimirov, Dmitry Pritykin and Danil Ivanov
The paper presents a study of decentralized control for a satellite formation flying mission that uses differential lift and drag to enforce the relative positioning requirements. All spacecraft are equipped with large sunlight reflectors so that, given ...
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Yu Chen, Qi Dong, Xiaozhou Shang, Zhenyu Wu and Jinyu Wang
Unmanned aerial vehicles (UAVs) are important in reconnaissance missions because of their flexibility and convenience. Vitally, UAVs are capable of autonomous navigation, which means they can be used to plan safe paths to target positions in dangerous su...
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Vasilios Patsias, Petros Amanatidis, Dimitris Karampatzakis, Thomas Lagkas, Kalliopi Michalakopoulou and Alexandros Nikitas
Task allocation in edge computing refers to the process of distributing tasks among the various nodes in an edge computing network. The main challenges in task allocation include determining the optimal location for each task based on the requirements su...
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Yankai Lv, Haiyan Ding, Hao Wu, Yiji Zhao and Lei Zhang
Federated learning (FL) is an emerging decentralized machine learning framework enabling private global model training by collaboratively leveraging local client data without transferring it centrally. Unlike traditional distributed optimization, FL trai...
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Dan Xu, Yunxiao Guo, Zhongyi Yu, Zhenfeng Wang, Rongze Lan, Runhao Zhao, Xinjia Xie and Han Long
Flocking for fixed-Wing Unmanned Aerial Vehicles (UAVs) is an extremely complex challenge due to fixed-wing UAV?s control problem and the system?s coordinate difficulty. Recently, flocking approaches based on reinforcement learning have attracted attenti...
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