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A distributed reinforcement learning approach for energy and congestion-aware edge networks
Proceedings of the 16th International Conference on emerging Networking EXperiments and Technologies
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10.1145/3386367.3431670
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2020
◽
Author(s):
Alessio Sacco
◽
Flavio Esposito
◽
Guido Marchetto
Keyword(s):
Reinforcement Learning
◽
Learning Approach
◽
Distributed Reinforcement
◽
Edge Networks
◽
Congestion Aware
Download Full-text
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References
A Distributed Reinforcement Learning Approach to In-network Congestion Control
2020 IEEE/CIC International Conference on Communications in China (ICCC)
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10.1109/iccc49849.2020.9238802
◽
2020
◽
Author(s):
Tianle Mai
◽
Haipeng Yao
◽
Xing Zhang
◽
Zehui Xiong
◽
Dusit Niyato
Keyword(s):
Reinforcement Learning
◽
Congestion Control
◽
Learning Approach
◽
Network Congestion
◽
Network Congestion Control
◽
Distributed Reinforcement
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Optimization of Resource Allocation in Multi-Cell OFDM Systems: A Distributed Reinforcement Learning Approach
2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications
◽
10.1109/pimrc48278.2020.9217276
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2020
◽
Author(s):
Yuntao Hu
◽
Ming Chen
◽
Zhaohui Yang
◽
Mingzhe Chen
◽
Guangyu Jia
Keyword(s):
Resource Allocation
◽
Reinforcement Learning
◽
Learning Approach
◽
Ofdm Systems
◽
Distributed Reinforcement
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Eco-Vehicular Edge Networks for Connected Transportation: A Distributed Multi-Agent Reinforcement Learning Approach
2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall)
◽
10.1109/vtc2020-fall49728.2020.9348507
◽
2020
◽
Author(s):
Md Ferdous Pervej
◽
Shih-Chun Lin
Keyword(s):
Reinforcement Learning
◽
Learning Approach
◽
Multi Agent
◽
Edge Networks
Download Full-text
Distributed Reinforcement Learning Approach for Vehicular Ad Hoc Networks
IEICE Transactions on Communications
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10.1587/transcom.e93.b.1431
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2010
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Vol E93-B
(6)
◽
pp. 1431-1442
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Cited By ~ 16
Author(s):
Celimuge WU
◽
Kazuya KUMEKAWA
◽
Toshihiko KATO
Keyword(s):
Reinforcement Learning
◽
Ad Hoc Networks
◽
Vehicular Ad Hoc Networks
◽
Ad Hoc
◽
Learning Approach
◽
Hoc Networks
◽
Distributed Reinforcement
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User association and power allocation for UAV-assisted networks: A distributed reinforcement learning approach
China Communications
◽
10.23919/jcc.2020.12.008
◽
2020
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Vol 17
(12)
◽
pp. 110-122
Author(s):
Xin Guan
◽
Yang Huang
◽
Chao Dong
◽
Qihui Wu
Keyword(s):
Reinforcement Learning
◽
Power Allocation
◽
User Association
◽
Learning Approach
◽
Distributed Reinforcement
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Aggregator election in wireless sensor networks: A distributed reinforcement learning approach
2013 13th Iranian Conference on Fuzzy Systems (IFSC)
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10.1109/ifsc.2013.6675637
◽
2013
◽
Author(s):
Maryam Hajishabani
◽
Mohammad Sadegh Kordafshari
◽
Mohammad Reza Meybodi
Keyword(s):
Wireless Sensor Networks
◽
Reinforcement Learning
◽
Sensor Networks
◽
Wireless Sensor
◽
Learning Approach
◽
Distributed Reinforcement
Download Full-text
A distributed reinforcement learning approach to maximize resource utilization and control handover dropping in multimedia wireless networks
The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications
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10.1109/pimrc.2002.1046544
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2003
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Cited By ~ 3
Author(s):
E. Alexandri
◽
G. Martinez
◽
D. Zeghlache
Keyword(s):
Wireless Networks
◽
Reinforcement Learning
◽
Resource Utilization
◽
Learning Approach
◽
Multimedia Wireless Networks
◽
And Control
◽
Distributed Reinforcement
Download Full-text
Multi-Agent Systems on Sensor Networks: A Distributed Reinforcement Learning Approach
2005 International Conference on Intelligent Sensors, Sensor Networks and Information Processing
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10.1109/issnip.2005.1595616
◽
2005
◽
Cited By ~ 5
Author(s):
Chen-Khong Tham
◽
J.-C. Renaud
Keyword(s):
Reinforcement Learning
◽
Sensor Networks
◽
Learning Approach
◽
Multi Agent Systems
◽
Agent Systems
◽
Multi Agent
◽
Distributed Reinforcement
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A Local Collaborative Distributed Reinforcement Learning Approach for Resource Allocation in V2X Networks
10.1007/978-3-030-86130-8_35
◽
2021
◽
pp. 442-454
Author(s):
Yue Zhang
◽
Guoping Tan
◽
Siyuan Zhou
Keyword(s):
Resource Allocation
◽
Reinforcement Learning
◽
Learning Approach
◽
Distributed Reinforcement
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A Distributed Reinforcement Learning approach for Power Control in Wireless Networks
2021 IEEE World AI IoT Congress (AIIoT)
◽
10.1109/aiiot52608.2021.9454208
◽
2021
◽
Author(s):
Antonio Ornatelli
◽
Andrea Tortorelli
◽
Francesco Liberati
Keyword(s):
Wireless Networks
◽
Reinforcement Learning
◽
Power Control
◽
Learning Approach
◽
Distributed Reinforcement
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