Multi-agent deep reinforcement learning for multi-robot applications: A survey
J Orr, A Dutta - Sensors, 2023 - mdpi.com
Deep reinforcement learning has produced many success stories in recent years. Some
example fields in which these successes have taken place include mathematics, games …
example fields in which these successes have taken place include mathematics, games …
Practical optimization and game theory for 6G ultra-dense networks: Overview and research challenges
Ultra-dense networks (UDNs) have been employed to solve the pressing problems in
relation to the increasing demand for higher coverage and capacity of the fifth generation …
relation to the increasing demand for higher coverage and capacity of the fifth generation …
Mean field deep reinforcement learning for fair and efficient UAV control
Unmanned aerial vehicles (UAVs) can provide flexible network coverage services. UAVs
can be applied in a large number of scenarios, such as emergency communication and …
can be applied in a large number of scenarios, such as emergency communication and …
Resource allocation for NOMA-MEC systems in ultra-dense networks: A learning aided mean-field game approach
Attracted by the advantages of multi-access edge computing (MEC) and non-orthogonal
multiple access (NOMA), this article studies the resource allocation problem of a NOMA …
multiple access (NOMA), this article studies the resource allocation problem of a NOMA …
Downlink transmit power control in ultra-dense UAV network based on mean field game and deep reinforcement learning
As an emerging technology in 5G, ultra-dense unmanned aerial vehicles (UAVs) network
can significantly improve the system capacity and networks coverage. However, it is still a …
can significantly improve the system capacity and networks coverage. However, it is still a …
Performance analysis of a delay constrained data offloading scheme in an integrated cloud-fog-edge computing system
R Fantacci, B Picano - IEEE Transactions on Vehicular …, 2020 - ieeexplore.ieee.org
The recent growth in intensive services and applications demand has triggered the
functional integration of cloud computing with edge computing capabilities. One of the main …
functional integration of cloud computing with edge computing capabilities. One of the main …
Mean field game guided deep reinforcement learning for task placement in cooperative multiaccess edge computing
Cooperative multiaccess edge computing (MEC) is a promising paradigm for the next-
generation mobile networks. However, when the number of users explodes, the …
generation mobile networks. However, when the number of users explodes, the …
Mean-field artificial noise assistance and uplink power control in covert IoT systems
In this paper, we study a covert Internet of Things (IoT) system. Compared with conventional
IoT systems that apply cryptography and information-theoretic secrecy approaches to secure …
IoT systems that apply cryptography and information-theoretic secrecy approaches to secure …
A mean field game-theoretic cross-layer optimization for multi-hop swarm UAV communications
T Li, C Li, C Yang, J Shao, Y Zhang… - Journal of …, 2021 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV) multi-hop communication networks are foreseen to be
widely employed in both military and civilian scenarios. However, in ultra-dense scenarios …
widely employed in both military and civilian scenarios. However, in ultra-dense scenarios …
Dynamic computation offloading in ultra-dense networks based on mean field games
R Zheng, H Wang, M De Mari, M Cui… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
In ultra-dense networks, the increasing popularity of computation intensive applications
imposes challenges to the resource-constrained smart mobile devices (SMDs), which may …
imposes challenges to the resource-constrained smart mobile devices (SMDs), which may …