… It can overcome the limitations of reinforcement learning, … reinforcement learning, namely
Deep Reinforcement Learning (DRL). DRL embraces the advantage of Deep Neural Networks (…

… Abstract—Future wireless communication networks tend to be … of deep reinforcement
learning for proactive caching[34-36] and coded caching[41]. We observe that deep reinforcement …

… DRL to wireless communication networks. An intelligent power algorithm model based on
deep neural networks (… ideas for the later development of the wireless communication field. …

… include deep reinforcement learning and wireless communications and networking. …
Systems, where he investigated fiber-optic communications networks. From 1988 to 1993, he was …

… through short-distance wireless communication. Using WSN networks has increased with the
… scheduling optimization in a maritime communications network based on Software Defined …

… and Networking Comprehensive guide to Deep Reinforcement Learning (… wireless
communication systems Deep Reinforcement Learning for Wireless Communications and …

… A standard SG is capable of carrying out a variety of tasks requiring the upgrade of both
the communication networks’ measuring and coordination facilities. It is essential to deploy …

… vehicle (UAV)-enabled wireless communication system, where … Deep Q-network (DDQN)
algorithm which introduces neural … for UAVaided communication networks,” IEEE Trans. …

… the use of Deep Reinforcement Learning, in particular, Deep Q learning, … deep learning
with Q learning, Deep Q learning or Deep Q Network (DQN) [5] can use a deep neural network …

… in wireless networks, … the wireless network edge using a deep reinforcement learning
framework with Wolpertinger architecture. In particular, we propose deep actor-critic reinforcement …