Reinforcement and deep reinforcement learning for wireless Internet of Things: A survey

MS Frikha, SM Gammar, A Lahmadi… - Computer Communications, 2021 - Elsevier
Nowadays, many research studies and industrial investigations have allowed the integration
of the Internet of Things (IoT) in current and future networking applications by deploying a …

Deep reinforcement learning for autonomous internet of things: Model, applications and challenges

L Lei, Y Tan, K Zheng, S Liu, K Zhang… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) extends the Internet connectivity into billions of IoT devices
around the world, where the IoT devices collect and share information to reflect status of the …

Deep reinforcement learning for Internet of Things: A comprehensive survey

W Chen, X Qiu, T Cai, HN Dai… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The incumbent Internet of Things suffers from poor scalability and elasticity exhibiting in
communication, computing, caching and control (4Cs) problems. The recent advances in …

Reinforcement-Learning-Based Routing and Resource Management for Internet of Things Environments: Theoretical Perspective and Challenges

A Musaddiq, T Olsson, F Ahlgren - Sensors, 2023 - mdpi.com
Internet of Things (IoT) devices are increasingly popular due to their wide array of
application domains. In IoT networks, sensor nodes are often connected in the form of a …

Learning paradigms for communication and computing technologies in IoT systems

W Ejaz, M Basharat, S Saadat, AM Khattak… - Computer …, 2020 - Elsevier
Wireless communication and computation technologies are becoming increasingly complex
and dynamic due to the sophisticated and ubiquitous Internet of things (IoT) applications …

An overview of intelligent wireless communications using deep reinforcement learning

Y Huang, C Xu, C Zhang, M Hua… - … of Communications and …, 2019 - ieeexplore.ieee.org
Future wireless communication networks tend to be intelligentized to accomplish the
missions that cannot be preprogrammed. In the new intelligent communication systems …

Deep reinforcement learning paradigm for dense wireless networks in smart cities

R Ali, YB Zikria, BS Kim, SW Kim - Smart cities performability, cognition, & …, 2020 - Springer
Wireless local area networks (WLANs) are widely deployed for Internet-centric data
applications. Due to their extensive norm in our day-to-day wireless-enabled life, WLANs are …

Deep reinforcement learning based resource management in UAV-assisted IoT networks

YY Munaye, RT Juang, HP Lin, GB Tarekegn, DB Lin - Applied Sciences, 2021 - mdpi.com
The resource management in wireless networks with massive Internet of Things (IoT) users
is one of the most crucial issues for the advancement of fifth-generation networks. The main …

DeepWiERL: Bringing deep reinforcement learning to the internet of self-adaptive things

F Restuccia, T Melodia - IEEE INFOCOM 2020-IEEE …, 2020 - ieeexplore.ieee.org
Recent work has demonstrated that cutting-edge advances in deep reinforcement learning
(DRL) may be leveraged to empower wireless devices with the much-needed ability to" …

Deep reinforcement learning for internet of drones networks: issues and research directions

N Aboueleneen, A Alwarafy… - IEEE Open Journal of the …, 2023 - ieeexplore.ieee.org
Internet of Drones (IoD) is one of the promising technologies to enhance the performance of
wireless networks. Deploying IoD to assist wireless networks, however, needs to address …