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

Heterogeneous networks (HetNets) have been regarded as the key technology for fifth
generation (5G) communications to support the explosive growth of mobile traffics. By …

Recent advances in Reinforcement Learning, grounded on combining classical theoretical
results with Deep Learning paradigm, led to breakthroughs in many artificial intelligence …

Artificial intelligence has made big steps forward with reinforcement learning (RL) in the last
century, and with the advent of deep learning (DL) in the 90s, especially, the breakthrough of …

Recently, we have seen a boom of attempts to improve the operation of networking protocols
using machine learning techniques. The proposed reinforcement learning (RL) based …

A hands-on guide enriched with examples to master deep reinforcement learning algorithms
with Python Key Features Your entry point into the world of artificial intelligence using the …

Due to the rapid development of network communication technology and the significant
increase in network terminal equipment, the application of new network architecture …

Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) are two
emerging paradigms that enable the feasible and scalable deployment of Virtual Network …

In wireless networks, context awareness and intelligence are capabilities that enable each
host to observe, learn, and respond to its complex and dynamic operating environment in an …

Routing optimization has long been a problem in the networking field. With the rapid
development of user applications, network traffic is continuously increasing in dynamicity …