Federated learning in mobile edge networks: A comprehensive survey
In recent years, mobile devices are equipped with increasingly advanced sensing and
computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up …
computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up …
An overview of multi-agent reinforcement learning from game theoretical perspective
Y Yang, J Wang - arXiv preprint arXiv:2011.00583, 2020 - arxiv.org
Following the remarkable success of the AlphaGO series, 2019 was a booming year that
witnessed significant advances in multi-agent reinforcement learning (MARL) techniques …
witnessed significant advances in multi-agent reinforcement learning (MARL) techniques …
Wireless network intelligence at the edge
J Park, S Samarakoon, M Bennis… - Proceedings of the …, 2019 - ieeexplore.ieee.org
Fueled by the availability of more data and computing power, recent breakthroughs in cloud-
based machine learning (ML) have transformed every aspect of our lives from face …
based machine learning (ML) have transformed every aspect of our lives from face …
Ultrareliable and low-latency wireless communication: Tail, risk, and scale
Ensuring ultrareliable and low-latency communication (URLLC) for 5G wireless networks
and beyond is of capital importance and is currently receiving tremendous attention in …
and beyond is of capital importance and is currently receiving tremendous attention in …
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 …
A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to AI-guided driving policy learning
This paper serves as an introduction and overview of the potentially useful models and
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
Ultra-dense networks: A survey
The exponential growth and availability of data in all forms is the main booster to the
continuing evolution in the communications industry. The popularization of traffic-intensive …
continuing evolution in the communications industry. The popularization of traffic-intensive …
Deep generalized schrödinger bridge
Abstract Mean-Field Game (MFG) serves as a crucial mathematical framework in modeling
the collective behavior of individual agents interacting stochastically with a large population …
the collective behavior of individual agents interacting stochastically with a large population …
Comprehensive review of deep reinforcement learning methods and applications in economics
The popularity of deep reinforcement learning (DRL) applications in economics has
increased exponentially. DRL, through a wide range of capabilities from reinforcement …
increased exponentially. DRL, through a wide range of capabilities from reinforcement …
[图书][B] The master equation and the convergence problem in mean field games:(ams-201)
P Cardaliaguet, F Delarue, JM Lasry, PL Lions - 2019 - books.google.com
This book describes the latest advances in the theory of mean field games, which are
optimal control problems with a continuum of players, each of them interacting with the …
optimal control problems with a continuum of players, each of them interacting with the …