A Double Q-Learning Approach for Navigation of Aerial Vehicles with Connectivity Constraint

ICC 2020 - 2020 IEEE International Conference on Communications (ICC) ◽

10.1109/icc40277.2020.9148608 ◽

2020 ◽

Author(s):

Behzad Khamidehi ◽

Elvino S. Sousa

Keyword(s):

Learning Approach ◽

Aerial Vehicles ◽

Connectivity Constraint

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DDQP: A Double Deep Q-Learning Approach to Online Fault-tolerant SFC Placement

IEEE Transactions on Network and Service Management ◽

10.1109/tnsm.2021.3049298 ◽

2021 ◽

pp. 1-1

Author(s):

Lei Wang ◽

Weixi Mao ◽

Jin Zhao ◽

Yuedong Xu

Keyword(s):

Fault Tolerant ◽

Learning Approach ◽

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Data-driven tracking control approach for linear systems by on-policy Q-learning approach

2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV) ◽

10.1109/icarcv50220.2020.9305479 ◽

2020 ◽

Author(s):

Zhang Yihan ◽

Xiao Zhenfei ◽

Li Jinna

Keyword(s):

Linear Systems ◽

Tracking Control ◽

Data Driven ◽

Learning Approach ◽

Control Approach ◽

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Dynamic traffic steering based on fuzzy Q-Learning approach in a multi-RAT multi-layer wireless network

Computer Networks ◽

10.1016/j.comnet.2014.06.003 ◽

2014 ◽

Vol 71 ◽

pp. 100-116 ◽

Author(s):

P. Muñoz ◽

D. Laselva ◽

R. Barco ◽

P. Mogensen

Keyword(s):

Wireless Network ◽

Learning Approach ◽

Dynamic Traffic ◽

Traffic Steering

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Dynamic Pricing Decision for Perishable Goods: A Q-Learning Approach

2008 4th International Conference on Wireless Communications, Networking and Mobile Computing ◽

10.1109/wicom.2008.2786 ◽

2008 ◽

Author(s):

Yan Cheng

Keyword(s):

Dynamic Pricing ◽

Learning Approach ◽

Perishable Goods ◽

Pricing Decision

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A Q-learning approach to automated unmanned air vehicle demining

The Journal of Defense Modeling and Simulation Applications Methodology Technology ◽

10.1177/1548512911414599 ◽

2011 ◽

Vol 9 (1) ◽

pp. 83-92 ◽

Author(s):

Silvia Ferrari ◽

Greyson Daugherty

Keyword(s):

Learning Approach ◽

Unmanned Air Vehicle ◽

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Aperiodic Sampled-Data Stabilization of Probabilistic Boolean Control Networks: Deep Q-learning Approach with Relaxed Bellman Operator

10.23919/ecc54610.2021.9655234 ◽

2021 ◽

Author(s):

Pratik Bajaria ◽

Amol Yerudkar ◽

Carmen Del Vecchio

Keyword(s):

Learning Approach ◽

Sampled Data ◽

Control Networks

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Blockchain-Based Software-Defined Industrial Internet of Things: A Dueling Deep ${Q}$ -Learning Approach

IEEE Internet of Things Journal ◽

10.1109/jiot.2018.2871394 ◽

2019 ◽

Vol 6 (3) ◽

pp. 4627-4639 ◽

Author(s):

Chao Qiu ◽

F. Richard Yu ◽

Haipeng Yao ◽

Chunxiao Jiang ◽

Fangmin Xu ◽

...

Keyword(s):

Internet Of Things ◽

Learning Approach ◽

Industrial Internet Of Things ◽

Industrial Internet

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Simulation of the operation of hydro plants in an electricity market using agent based models - introducing a Q Learning approach

2016 13th International Conference on the European Energy Market (EEM) ◽

10.1109/eem.2016.7521334 ◽

2016 ◽

Author(s):

Jose Carlos Sousa ◽

Joao Tome Saraiva

Keyword(s):

Electricity Market ◽

Learning Approach ◽

Agent Based Models ◽

Agent Based ◽

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A Cooperative Q-Learning Approach for Online Power Allocation in Femtocell Networks

2013 IEEE 78th Vehicular Technology Conference (VTC Fall) ◽

10.1109/vtcfall.2013.6692027 ◽

2013 ◽

Author(s):

Hussein Saad ◽

Amr Mohamed ◽

Tamer ElBatt

Keyword(s):

Power Allocation ◽

Learning Approach ◽

Femtocell Networks ◽

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Q-learning Approach for Load-balancing in Software Defined Networks

2018 Moratuwa Engineering Research Conference (MERCon) ◽

10.1109/mercon.2018.8421895 ◽

2018 ◽

Author(s):

Deepal Tennakoon ◽

Suneth Karunarathna ◽

Brian Udugama

Keyword(s):

Load Balancing ◽

Learning Approach ◽

Software Defined Networks ◽

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