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This paper proposes a novel centralized training and distributed execution(CTDE)-based multi-agent deep reinforcement learning (MADRL) method formultiple unmanned aerial vehicles (UAVs) control in autonomous mobile accessapplications. For the purpose, a single neural network is utilized incentralized training for cooperation among multiple agents while maximizing thetotal quality of service (QoS) in mobile access applications.

Coordinated Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Swarms in Autonomous Mobile Access Applications