Poster: Coordinated Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Swarms in Autonomous Mobile Access Applications - Park, Chanyoung; Lee, Haemin; Yun, Won Joon; Park, Soohyun; Jung, Soyi; Kim, Joongheon (Proceedings - International Conference on Distributed Computing Systems, 2023)
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.
Keywords: Access applications; Aerial vehicle; Autonomous mobilities; Mobile access; Multi agent; Multi agent deep reinforcement learning; Non terrestrial network; Reinforcement learnings; Terrestrial networks; Unmanned aerial vehicle; Autonomous mobility; Multi agent deep reinforcement learning (MADRL); Non Terrestrial Network (NTN); Unmanned aerial vehicle (UAV)