Graphon Mean Field Games and the GMFG Equations
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Abstract (arXiv)
The emergence of the graphon theory of large networks and their infinite limits has enabled the formulation of a theory of the centralized control of dynamical systems distributed on asymptotically infinite networks (Gao and Caines, IEEE CDC 2017, 2018). Furthermore, the study of the decentralized control of such systems was initiated in (Caines and Huang, IEEE CDC 2018, 2019), where Graphon Mean Field Games (GMFG) and the GMFG equations were formulated for the analysis of non-cooperative dynamic games on unbounded networks. In that work, existence and uniqueness results were introduced for the GMFG equations, together with an epsilon-Nash theory for GMFG systems which relates infinite population equilibria on infinite networks to finite population equilibria on finite networks. Those results are rigorously established in this paper.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Aug 2020.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 2; 2025: 3; 2026: 3.
11 papers.
- 2024Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithmcited by 5
- 2026Learning operators on labelled conditional distributions with applications to mean field control of non exchangeable systemscited by 3
- 2025Learning Mean Field Control on Sparse Graphscited by 2
- 2023Reinforcement Learning for SBM Graphon Games with Re-Samplingcited by 1
- 2025Convergence and Connectivity: Dynamics of Multi-Agent Q-Learning in Random Networkscited by 1
- 2025Policy Optimization for Continuous-time Linear-Quadratic Graphon Mean Field Gamescited by 1
- 2026Graphon Mean-Field Subsampling for Cooperative Heterogeneous Multi-Agent Reinforcement Learningcited by 1
- 2022Fixed-Point Centrality for Networkscited by 0
- 2023Sparse Mean Field Load Balancing in Large Localized Queueing Systemscited by 0
- 2024Graphon Particle Systems, Part II: Dynamics of Distributed Stochastic Continuum Optimizationcited by 0
- 2026Mean-Field Control on Sparse Graphs: From Local Limits to GNNs via Neighborhood Distributionscited by 0
- 2026Learning operators on labelled conditional distributions with applications to mean field control of non exchangeable systems23 Mar 2026
- 2026Graphon Mean-Field Subsampling for Cooperative Heterogeneous Multi-Agent Reinforcement Learning18 Feb 2026
- 2026Mean-Field Control on Sparse Graphs: From Local Limits to GNNs via Neighborhood Distributions29 Jan 2026
- 2025Policy Optimization for Continuous-time Linear-Quadratic Graphon Mean Field Games6 Jun 2025
- 2025Convergence and Connectivity: Dynamics of Multi-Agent Q-Learning in Random Networks13 Mar 2025
- 2025Learning Mean Field Control on Sparse Graphs28 Jan 2025
- 2024Graphon Particle Systems, Part II: Dynamics of Distributed Stochastic Continuum Optimization3 Jul 2024
- 2024Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm8 May 2024
- 2023Sparse Mean Field Load Balancing in Large Localized Queueing Systems20 Dec 2023
- 2023Reinforcement Learning for SBM Graphon Games with Re-Sampling25 Oct 2023
- 2022Fixed-Point Centrality for Networks15 Sep 2022