… change if there is a communication failure, while the UAVs still execute the policies learned
while communicating perfectly? In this paper, two communication failures are assumed here: …

… However, since the existing congestion control (CC) mechanisms of MPTCP fail to distin…
mechanism targeted at SGINHSR based on deep reinforcement learning, which is referred to as …

… With the continuous development of wireless communication … failures while minimizing
detection time. COC executes actions to mitigate or at least alleviate the effect of the failure [2]. In …

… MDP), and propose a deep reinforcement learning (DRL) based framework… communication
Transformer (CT) as a backbone of SACCT by representing network states as communication …

… Implementation of advanced communications infrastructure in … of Reinforcement Learning
(RL) and Deep Reinforcement … in order to avoid cascading failures and possible blackouts/…

Grant-free non-orthogonal multiple access (GF-NOMA) is a potential technique to support
massive Ultra-Reliable and Low-Latency Communication (mURLLC) service. However, the …

… VRA in 5G NR C-V2X sidelink communication based on network slicing and NOMA. To do
so, we apply deep reinforcement learning (DRL) [24]. In general, deep learning (DL) has had …

… , deep reinforcement learning has the advantages of high precision and high learning efficiency.
Consequently, this article uses a new deep reinforcement … by internal component failure, …

… Then, we propose a deep reinforcement … radarcommunications system in AVs. With the
MDP framework, the AV can adaptively select the radar detection function or data communication …

… In this paper, we propose an offline scheme based on double deep reinforcement learning
(DDRL) to minimize the frequency of HOs in mm-wave networks, which subsequently …