ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2209.03854
  4. Cited By
Optimal Offloading Strategies for Edge-Computing via Mean-Field Games
  and Control

Optimal Offloading Strategies for Edge-Computing via Mean-Field Games and Control

8 September 2022
Kai Cui
M. Yilmaz
Anam Tahir
A. Klein
Heinz Koeppl
ArXivPDFHTML

Papers citing "Optimal Offloading Strategies for Edge-Computing via Mean-Field Games and Control"

4 / 4 papers shown
Title
Joint D2D Collaboration and Task Offloading for Edge Computing: A Mean
  Field Graph Approach
Joint D2D Collaboration and Task Offloading for Edge Computing: A Mean Field Graph Approach
Xiong Wang
Jiancheng Ye
John C. S. Lui
23
3
0
03 May 2021
Discrete-Time Mean Field Control with Environment States
Discrete-Time Mean Field Control with Environment States
Kai Cui
Anam Tahir
Mark Sinzger
Heinz Koeppl
AI4CE
42
13
0
30 Apr 2021
Multi-Agent Reinforcement Learning: A Selective Overview of Theories and
  Algorithms
Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms
Kai Zhang
Zhuoran Yang
Tamer Basar
181
1,213
0
24 Nov 2019
On the Convergence of Model Free Learning in Mean Field Games
On the Convergence of Model Free Learning in Mean Field Games
Romuald Elie
Julien Pérolat
Mathieu Laurière
Matthieu Geist
Olivier Pietquin
55
91
0
04 Jul 2019
1