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Discrete Event Dynamic Modeling and Analysis of the Democratic Progress in a Society Controlled by Networked Agents
  • 2022-01-01
  • IEEE Transactions on Automatic Control, Vol.67, pp.359-365
  • Institute of Electrical and Electronics Engineers Inc.
Achieving a global objective with competing networked agents in the framework of discrete event systems
  • 2020-04-02
  • International Journal of Control, Vol.93, pp.889-897
  • Taylor and Francis Ltd.
Convergence of a Democratic System Controlled by Dynamic Social Networks
  • 2024-07-01
  • International Journal of Control, Automation and Systems, Vol.22, pp.2055-2063
  • Institute of Control, Robotics and Systems
Context-aware pub/sub control method using reinforcement learning
  • 2021-08-10
  • Concurrency and Computation: Practice and Experience, Vol.33
  • John Wiley and Sons Ltd
HiMAQ: Hierarchical multi-agent Q-learning-based throughput and fairness improvement for UAV-Aided IoT networks
  • 2024-03-01
  • Journal of Network and Computer Applications, Vol.223
  • Academic Press
Energy Efficient Power Allocation in Massive MIMO Based on Parameterized Deep DQNoa mark
  • 2023-11-01
  • Electronics (Switzerland), Vol.12
  • Multidisciplinary Digital Publishing Institute (MDPI)
MUSCAT: Distributed multi-agent Q-learning-based minimum span channel allocation technique for UAV-enabled wireless networks
  • Lee, Ki Hun;
  • Lee, Seungmin;
  • Park, Jaedon;
  • Lee, Howon;
  • Jung, Bang Chul
  • 2024-06-01
  • Computer Networks, Vol.247
  • Elsevier B.V.
Policy-Based Hybrid Wireless Network Management
  • Siddiqui, Faisal Adeem
  • 2005-08
  • The Graduate School, Ajou University
Cooperative Multi-UAV Positioning for Aerial Internet Service Management: A Multi-Agent Deep Reinforcement Learning Approach
  • Kim, Joongheon;
  • Park, Soohyun;
  • Jung, Soyi;
  • Cordeiro, Carlos
  • 2024-01-01
  • IEEE Transactions on Network and Service Management, Vol.21, pp.3797-3812
  • Institute of Electrical and Electronics Engineers Inc.
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