EDP Sciences logo
Subscriber Authentication Point
Search
Menu
All issues Volume 32 (2026) ESAIM: COCV, 32 (2026) 34 References
Open Access
Issue
ESAIM: COCV
Volume 32, 2026
Article Number 34
Number of page(s) 26
DOI https://doi.org/10.1051/cocv/2026017
Published online 23 April 2026
  1. R. Carmona and F. Delarue, Probabilistic Theory of Mean Field Games with Applications, Vols. I—II. Springer-Verlag, New York (2018). [Google Scholar]
  2. A. Bensoussan, J. Frehse and P. Yam, Mean Field Games and Mean Field Type Control Theory. Springer Briefs in Mathematics (2013). [Google Scholar]
  3. J. Yong, A linear-quadratic optimal control problem for mean-field stochastic differential equations. SIAM J. Control Optim. 51 (2013) 2809–2838. [Google Scholar]
  4. J. Huang, X. Li and J. Yong, A linear-quadratic optimal control problem for mean-field stochastic differential equations in infinite horizon. Math. Control Related Fields 5 (2015) 97–139. [CrossRef] [MathSciNet] [Google Scholar]
  5. J. Sun, Mean-field stochastic linear quadratic optimal control problems: Open-loop solvabilities. ESAIM Control Optim. Calc. Var. 23 (2017) 1099–1127. [Google Scholar]
  6. M. Basei and H. Pham, A weak martingale approach to linear-quadratic McKean-Vlasov stochastic control problems. J. Optim. Theory Appl. 181 (2019) 347–382. [CrossRef] [MathSciNet] [Google Scholar]
  7. L. Lovasz, Large Networks and Graph Limits, Vol. 60 of American Mathematical Society Colloquium Publications. American Mathematical Society, Providence, RI (2012). [Google Scholar]
  8. E. Bayraktar, S. Chakraborty and R. Wu, Graphon mean field systems. Ann. Appl. Probab. 33 (2023) 3587–3619. [Google Scholar]
  9. F. Coppini, A. Crescenzo and H. Pham, Nonlinear graphon mean-field systems. Stochastic Process. Appl. 190 (2025) Paper No. 104728, 19. [Google Scholar]
  10. P.-E. Jabin, D. Poyato and J. Soler, Mean-field limit of non-exchangeable systems. Comm. Pure Appl. Math. 78 (2025) 651–741. [Google Scholar]
  11. C. Crucianelli and L. Tangpi, Interacting particle systems on sparse w-random graphs. (2024) arXiv:2410.11240. [Google Scholar]
  12. A. Aurell, R. Carmona and M. Lauriere, Stochastic graphon games: II, the linear quadratic case. Appl. Math. Optim. Vol. 85 (2022). [Google Scholar]
  13. P.E. Caines and M. Huang, Graphon mean field games and their equations. SIAM J. Control Optim. 59 (2020) 4373–4399. [Google Scholar]
  14. D. Lacker and A. Soret, A label-state formulation of stochastic graphon games and approximate equilibria on large networks. Math. Oper. Res. 48 (2023) 1987–2018. [Google Scholar]
  15. D.-x. Xu, Z. Gou, N.-j. Huang and S. Gao, Linear-quadratic graphon mean field games with common noise. 63 (2025) 3526–3556. [Google Scholar]
  16. X. Feng, Y. Hu and J. Huang, A unified approach to linear-quadratic-Gaussian mean-field team: homogeneity, heterogeneity and quasi-exchangeability. Ann. Appl. Probab. 33 (2023) 2786–2823. [Google Scholar]
  17. A. De Crescenzo, M. Fuhrman, I. Kharroubi and H. Pham, Mean-field control of non exchangeable systems. ESAIM Control Optim. Calc. Var. 32 (2026) Paper No. 3. [Google Scholar]
  18. J. Yong and X.Y. Zhou, Stochastic Controls: Hamiltonian Systems and HJB Equations, Vol. 43. Springer-Verlag, New York (1999). [Google Scholar]
  19. S. Peng, Stochastic Hamilton-Jacobi-Bellman equations. SIAM J. Control Optim. 30 (1992) 284–304. [CrossRef] [MathSciNet] [Google Scholar]
  20. G. Tessitore, Some remarks on the Riccati equation arising in an optimal control problem with state- and control- dependent noise. SIAM J. Control Optim. 30 (1992) 717–744. [Google Scholar]
  21. G. Guatteri and G. Tessitore, On the backward stochastic Riccati equation in infinite dimensions. SIAM J. Control Optim. 44 (2005) 159–194. [Google Scholar]
  22. Y. Hu and S. Tang, Stochastic LQ control and associated Riccati equation of PDEs driven by state- and control- dependent white noise. SIAM J. Control Optim. 60 (2022) 435–457. [Google Scholar]
  23. E. Abi Jaber, E. Miller and H. Pham, Linear-quadratic control for a class of stochastic Volterra equations: solvability and approximation. Ann. Appl. Probab. 31 (2021) 2244–2274. [MathSciNet] [Google Scholar]
  24. R. Carmona, J.-P. Fouque and L.-H. Sun, Mean field games and systemic risk. Commun. Math. Sci. 13 (2015) 911–933. [Google Scholar]
  25. A. Cosso, F. Gozzi I. Kharroubi, H. Pham and M. Rosestolato, Optimal control of path-dependent McKean-Vlasov SDEs in infinite-dimension. Ann. Appl. Probab. 33 (2023) 2863–2918. [MathSciNet] [Google Scholar]
  26. S. Federico, D. Ghilli and F. Gozzi, Linear-quadratic mean field games in hilbert spaces. SIAM J. Math. Anal. 57 (2025) 5821–5853. [Google Scholar]
  27. H. Liu and D. Firoozi, Hilbert space-valued lq mean field games: an infinite-dimensional analysis. SIAM J. Control Optim. 63 (2025) 3297–3327. [Google Scholar]
  28. G. Fabbri, F. Gozzi and A. Swiech, Stochastic optimal control in infinite dimension, Vol. 82 of Probability Theory and Stochastic Modelling. Springer, Cham (2017). Dynamic programming and HJB equations, With a contribution by Marco Fuhrman and Gianmario Tessitore. [Google Scholar]
  29. Y. Sun. The exact law of large numbers via Fubini extension and characterization of insurable risks. J. Econom. Theory 126 (2006) 31–69. [Google Scholar]
  30. E. Zeidler, Nonlinear Functional Analysis and its Applications. Springer-Verlag, New York (1986). Fixed-point theorems. Translated from German, originally published by Teubner, Leipzig (1976). [Google Scholar]
  31. L.-H. Sun, Mean field games with heterogeneous groups: application to banking systems. J. Optim. Theory Appl. 192 (2022) 130–167. [Google Scholar]
  32. H. Pham and X. Wei, Bellman equation and viscosity solutions for mean-field stochastic control problem. ESAIM Control Optim. Calc. Var. 24 (2018) 437–461. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.