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