Energy Efficient Edge Computing: When Lyapunov Meets Distributed Reinforcement Learning

31 March 2021

Papers citing "Energy Efficient Edge Computing: When Lyapunov Meets Distributed Reinforcement Learning"

5 / 5 papers shown

Title
A Reinforcement Learning Formulation of the Lyapunov Optimization: Application to Edge Computing Systems with Queue Stability Sohee Bae Seungyul Han Y. Sung 64 9 0 14 Dec 2020
Multi-Agent Reinforcement Learning for Adaptive User Association in Dynamic mmWave Networks Mohamed Sana A. De Domenico Wei Yu Y. Lostanlen Emilio Calvanese Strinati 35 55 0 16 Jun 2020
A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art Quoc-Viet Pham Fang Fang H. Vu Md. Jalil Piran Mai Le L. Le Won Joo Hwang Z. Ding 47 600 0 20 Jun 2019
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 241 18,685 0 20 Jul 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 484 129,831 0 12 Jun 2017