This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …

Future-generation wireless networks (5G and beyond) must accommodate surging growth in
mobile data traffic and support an increasingly high density of mobile users involving a …

Future Internet involves several emerging technologies such as 5G and beyond 5G
networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of …

In recent years, intelligent communication has drawn huge research efforts in both academia
and industry. With the advent of 5G technology, intelligent wireless terminals and intelligent …

Recent advances in Deep Reinforcement Learning (DRL) techniques are providing a
dramatic improvement in decision-making and automated control problems. As a result, we …

Deep Reinforcement Learning (DRL) has recently witnessed significant advances that have
led to multiple successes in solving sequential decision-making problems in various …

After decades of unprecedented development, modern networks have evolved far beyond
expectations in terms of scale and complexity. In many cases, traditional traffic engineering …

Abstract Deep Reinforcement Learning (DRL) has shown a dramatic improvement in
decision-making and automated control problems. Consequently, DRL represents a …

Deep Reinforcement Learning (DRL) is a powerful technique for learning policies for
complex decision-making tasks. In this paper, we provide an overview of DRL, including its …

Deep reinforcement learning (DRL) has recently revolutionized the resolution of decision-
making and automated control problems. In the context of networking, there is a growing …