… -terrestrial integrated maritime networks is constructed as a reinforcement learning system.
… Then we adopt a deep reinforcement learning approach to resolve the optimization problem …

… computation in this maritime UAV swarm mobile edge computing network. We reformulate …
, we take deep reinforcement learning (DRL) as our tool to propose a deep Q-network (DQN) …

… maritime wireless networks, we have constructed a software-defined maritime communication
network … heterogeneous networks that can effectively simplify the packet core network and …

… algorithm with the enhanced deep Q-learning algorithm. The main contributions of this …
-defined maritime communication network framework which integrates the network deployment of …

… combines reinforcement learning with deep learning, where deep learning can employ
neural networks to estimate the Qvalue of state s and action a [41]. Furthermore, to prevent the …

… maritime environments is difficult to optimize. In this paper, a reinforcement learning-based
UAV relay policy for maritime … the Bit-Error-Rate (BER) of the maritime signals. A deep …

… However, MASS navigation in complex maritime traffic presents challenges, especially in …
on safe reinforcement learning (SRL) with a reliability and risk hierarchical critic network (SRL-…

… the maritime communication and even cause the maritime tracking and monitoring task failure.
In this paper, we propose a deep reinforcement learning based maritime … neutral networks …

… overview of IALA Maritime Buoyage System, and Section 3 provides the mathematical model
design. Section 4 introduces the model of deep reinforcement learning network. Simulation …

… a satellite-based 6G maritime communication network with additional resources. In our
proposed architecture, we provide resources to the maritime 6G communication network, where a …