… We propose two algorithms for designing the trajectory of the UAV and analyze the impact
… The UAV is modeled as a deep reinforcement learning (DRL) agent to learn how to move by …

… In this paper, a novel DQN model for an optimal deployment and trajectory design of a UAV-…
In addition, they demonstrate that 3D trajectory design of UAV-BS is possible using the DQN…

… design their trajectories in a distributed manner and optimize their trajectory design policies
by learning from previous design … , we adopt deep reinforcement learning approaches in this …

… Specifically, inspired by the state-of-the-art deep reinforcement … deep deterministic policy
gradient (TD3) to design the UAV’s trajectory and we present a TD3-based trajectory design for …

… 3D UAV trajectory design and band … a deep reinforcement learning (DRL)-based algorithm,
named as EEFC-TDBA (energy-efficient fair communication through trajectory design and …

… trajectory design policy of [35] [36], the trajectory of UAVs in this paper is not with a fixed
destination. Thus, our contributions are as follows: r We design … Deep reinforcement learning (…

… This paper studied multi-UAV trajectory design problem for uplink data collection task based
on multi-agent DRL algorithm. The trajectories of UAVs were jointly optimized to minimize …

… of joint trajectory design and power allocation (JTDPA) issue, it is challenging to attain the
optimal joint policy in multi-UAV networks. In this paper, a multi-agent deep reinforcement …

… allocation and trajectory design problem … reinforcement learning and deep learning to
design the optimal policy of all the UAVs. Then, we also present a multi-agent deep reinforcement …

… on either UAV trajectory design with fixed GU access or GU access control given predefined
UAV trajectory. In this article, we optimize both UAV trajectory design and GU access control …