# Mean-Field-Type Games in Engineering

arXiv: https://arxiv.org/abs/1605.03281 · HTML: https://mlsanity.com/paper/1605.03281/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 May 2016.

## Built on by (most cited first, 11 of 11)

- [Learning Graphon Mean Field Games and Approximate Nash Equilibria](https://mlsanity.com/paper/2112.01280/) (2021)
- [Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL](https://mlsanity.com/paper/2402.05724/) (2024)
- [Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behavior](https://mlsanity.com/paper/2307.06175/) (2023)
- [Learning Correlated Equilibria in Mean-Field Games](https://mlsanity.com/paper/2208.10138/) (2022)
- [Major-Minor Mean Field Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/2303.10665/) (2023)
- [Hypergraphon Mean Field Games](https://mlsanity.com/paper/2203.16223/) (2022)
- [High-dimensional Mean-Field Games by Particle-based Flow Matching](https://mlsanity.com/paper/2512.01172/) (2025)
- [Learning Discrete-Time Major-Minor Mean Field Games](https://mlsanity.com/paper/2312.10787/) (2023)
- [Reinforcement Learning for Finite Space Mean-Field Type Games](https://mlsanity.com/paper/2409.18152/) (2024)
- [Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics](https://mlsanity.com/paper/2510.22158/) (2025)
- [Bounded Rationality Equilibrium Learning in Mean Field Games](https://mlsanity.com/paper/2411.07099/) (2024)

## 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.