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

The end-to-end quality of service (QoS) and quality of experience (QoE) guarantee is quite
important for network optimization. The current 5G and conceived 6G network in the future …

Abstract Machine Learning (ML) has been enjoying an unprecedented surge in applications
that solve problems and enable automation in diverse domains. Primarily, this is due to the …

While neural networks have achieved high accuracy on standard image classification
benchmarks, their accuracy drops to nearly zero in the presence of small adversarial …

Resource management problems in systems and networking often manifest as difficult
online decision making tasks where appropriate solutions depend on understanding the …

These days, taking the revolutionary approach of using clean-slate learning-based designs
to completely replace the classic congestion control schemes for the Internet is gaining …

While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …

This book presents an overview of formal decision making methods for decentralized
cooperative systems. It is aimed at graduate students and researchers in the fields of …

Recently, machine learning has been used in every possible field to leverage its amazing
power. For a long time, the networking and distributed computing system is the key …

We describe the results of a randomized controlled trial of video-streaming algorithms for
bitrate selection and network prediction. Over the last year, we have streamed 38.6 years of …