mlsanityData to 7 Oct 2026

Mean-Field-Type Games in Engineering

arXiv 1605.03281 ↗First posted 11 May 2016math.OC cs.GTcited by 11

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Abstract (arXiv)

A mean-field-type game is a game in which the instantaneous payoffs and/or the state dynamics functions involve not only the state and the action profile but also the joint distributions of state-action pairs. This article presents some engineering applications of mean-field-type games including road traffic networks, multi-level building evacuation, millimeter wave wireless communications, distributed power networks, virus spread over networks, virtual machine resource management in cloud networks, synchronization of oscillators, energy-efficient buildings, online meeting and mobile crowdsensing.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 May 2016.

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Citing papers per year: 2021: 1; 2022: 2; 2023: 3; 2024: 3; 2025: 2.

11 papers.

  1. 2021Learning Graphon Mean Field Games and Approximate Nash Equilibriacited by 28
  2. 2024Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RLcited by 9
  3. 2023Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behaviorcited by 6
  4. 2022Learning Correlated Equilibria in Mean-Field Gamescited by 4
  5. 2023Major-Minor Mean Field Multi-Agent Reinforcement Learningcited by 4
  6. 2022Hypergraphon Mean Field Gamescited by 3
  7. 2025High-dimensional Mean-Field Games by Particle-based Flow Matchingcited by 3
  8. 2023Learning Discrete-Time Major-Minor Mean Field Gamescited by 2
  9. 2025Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamicscited by 2
  10. 2024Reinforcement Learning for Finite Space Mean-Field Type Gamescited by 1
  11. 2024Bounded Rationality Equilibrium Learning in Mean Field Gamescited by 0