A survey on the convergence of edge computing and AI for UAVs: Opportunities and challenges

P McEnroe, S Wang, M Liyanage - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
The latest 5G mobile networks have enabled many exciting Internet of Things (IoT)
applications that employ unmanned aerial vehicles (UAVs/drones). The success of most …

Multi-agent reinforcement learning: A review of challenges and applications

L Canese, GC Cardarilli, L Di Nunzio, R Fazzolari… - Applied Sciences, 2021 - mdpi.com
In this review, we present an analysis of the most used multi-agent reinforcement learning
algorithms. Starting with the single-agent reinforcement learning algorithms, we focus on the …

Multi-agent reinforcement learning: A selective overview of theories and algorithms

K Zhang, Z Yang, T Başar - Handbook of reinforcement learning and …, 2021 - Springer
Recent years have witnessed significant advances in reinforcement learning (RL), which
has registered tremendous success in solving various sequential decision-making problems …

Single and multi-agent deep reinforcement learning for AI-enabled wireless networks: A tutorial

A Feriani, E Hossain - IEEE Communications Surveys & …, 2021 - ieeexplore.ieee.org
Deep Reinforcement Learning (DRL) has recently witnessed significant advances that have
led to multiple successes in solving sequential decision-making problems in various …

Multi-agent DRL for task offloading and resource allocation in multi-UAV enabled IoT edge network

AM Seid, GO Boateng, B Mareri… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) edge network has connected lots of heterogeneous smart
devices, thanks to unmanned aerial vehicles (UAVs) and their groundbreaking emerging …

Aerial imagery pile burn detection using deep learning: The FLAME dataset

A Shamsoshoara, F Afghah, A Razi, L Zheng, PZ Fulé… - Computer Networks, 2021 - Elsevier
Wildfires are one of the costliest and deadliest natural disasters in the US, causing damage
to millions of hectares of forest resources and threatening the lives of people and animals. Of …

Applications of multi-agent reinforcement learning in future internet: A comprehensive survey

T Li, K Zhu, NC Luong, D Niyato, Q Wu… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Future Internet involves several emerging technologies such as 5G and beyond 5G
networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of …

SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach

S Mousavi, F Afghah, UR Acharya - PloS one, 2019 - journals.plos.org
Electroencephalogram (EEG) is a common base signal used to monitor brain activities and
diagnose sleep disorders. Manual sleep stage scoring is a time-consuming task for sleep …

A survey on machine-learning techniques for UAV-based communications

PS Bithas, ET Michailidis, N Nomikos, D Vouyioukas… - Sensors, 2019 - mdpi.com
Unmanned aerial vehicles (UAVs) will be an integral part of the next generation wireless
communication networks. Their adoption in various communication-based applications is …

Machine learning-aided operations and communications of unmanned aerial vehicles: A contemporary survey

H Kurunathan, H Huang, K Li, W Ni… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Over the past decade, Unmanned Aerial Vehicles (UAVs) have provided pervasive, efficient,
and cost-effective solutions for data collection and communications. Their excellent mobility …