Abstract
A linear quadratic (LQ) stochastic optimization problem with delay involving weakly-coupled large population is investigated in this paper. Different to classic mean field (MF) game, here agents cooperate with each other to minimize the so-called social objective. With the aid of delayed person-by-person optimality principle, one arrives at an auxiliary LQ delayed control problem by decentralized information. A decentralized strategy is obtained by feat of an MF type anticipated forward-backward stochastic differential delay equation (AFBSDDE) consistency condition. The discounting method with delay feature is employed to solve the consistency condition system. Finally, by some estimates of AFBSDDEs we derive the asymptotic social optimality.
We’re sorry, something doesn't seem to be working properly.
Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.
References
Arabneydi, J., Mahajan, A.: Team-optimal solution of finite number of mean-field coupled LQG subsystems. In: 2015 54th IEEE Conference on Decision and Control (CDC). IEEE, 5308–5313 (2015)
Barreiro-Gomez, J., Duncan, T., Tembine, H.: Linear-quadratic mean-field-type games: jump-diffusion process with regime switching. IEEE Trans. Autom. Control 64, 4329–4336 (2019)
Bensoussan, A., Sung, K., Yam, S., Yung, S.: Linear-quadratic mean field games. J. Optim. Theory Appl. 169, 496–529 (2016)
Buckdahn, R., Li, J., Peng, S.: Mean-field backward stochastic differential equations and related partial differential equations. Stochastic Process. Appl. 119, 3133–3154 (2009)
Buckdahn, R., Li, J., Peng, S.: Catherine Rainer. Mean-field stochastic differential equations and associated PDEs. Ann. Probab. 45, 824–878 (2017)
Carmona, R., Delarue, F.: Probabilistic analysis of mean-field games. SIAM J. Control. Optim. 51, 2705–2734 (2013)
Chen, L., Wu, Z.: Maximum principle for the stochastic optimal control problem with delay and application. Automatica 46, 1074–1080 (2010)
Chen, Y., Bušić, A., Meyn, S.P.: State estimation for the individual and the population in mean field control with application to demand dispatch. IEEE Trans. Autom. Control 62, 1138–1149 (2016)
Darling, R., Pardoux, E.: Backward SDE with random terminal time and applications to semilinear elliptic PDE. Ann. Probab. 25, 1135–1159 (1997)
Du, K., Wu, Z.: Social optima in mean field linear-quadratic-Gaussian models with control input constraint. Syst. Control Lett. 162, 105174 (2022)
Feng, X., Huang, J., Wang, S.: Social optima of backward linear-quadratic-Gaussian mean-field teams. Appl. Math. Optim. 84, S651–S694 (2021)
Hu, Y., Huang, J., Nie, T.: Linear-Quadratic-Gaussian mixed mean-field games with heterogeneous input constraints. SIAM J. Control. Optim. 56, 2835–2877 (2018)
Huang, J., Li, N.: Linear-quadratic mean-field game for stochastic delayed systems. IEEE Trans. Autom. Control 63, 2722–2729 (2018)
Huang, J., Wang, B., Yong, J.: Social optima in mean field linear-quadratic-Gaussian control with volatility uncertainty. SIAM J. Control. Optim. 59, 825–856 (2021)
Huang, M., Nguyen, S.: Linear-Quadratic Mean Field Social Optimization with a Major Player. arXiv preprint arXiv: 1904.03346 (2019)
Huang, M., Caines, P.E., Malhamé, R.P.: Social optima in mean field LQG control: centralized and decentralized strategies. IEEE Trans. Autom. Control 57, 1736–1751 (2012)
Lasry, J.M., Lions, P.L.: Mean field games. Jpn. J. Math. 2, 229–260 (2007)
Mao, X.: Stochastic Differential Equations and Their Applications. Horwood, New York (1997)
Menoukeu-Pamen, O.: Optimal control for stochastic delay system under model uncertainty: a stochastic differential game approach. J. Optim. Theory Appl. 167, 998–1031 (2015)
Nguyen, S., Nguyen, D., Yin, G.: A stochastic maximum principle for switching diffusions using conditional mean-fields with applications to control problems. ESAIM Control Optim. Calc. Var. 26, 1–26 (2020)
Nie, T., Wang, S., Wu, Z.: Appendices: Linear-quadratic delayed mean-field social optimization. arXiv preprint arXiv:2301.06022 (2023)
Nourian, M., Caines, P.E.: \(\epsilon \)-Nash mean field game theory for nonlinear stochastic dynamical systems with major and minor agents. SIAM J. Control. Optim. 51, 3302–3331 (2013)
Nuno, G., Moll, B.: Social optima in economies with heterogeneous agents. Rev. Econ. Dyn. 28, 150–180 (2018)
Øksendal, B., Sulem, A.: A maximum principle for optimal control of stochastic systems with delay, with applications to finance. Optimal Control and Partial Differential Equations, Conference, pp. 64–79 (2001)
Øksendal, B., Sulem, A.: Optimal stochastic impulse control with delayed reaction. Appl. Math. Optim. 58, 243–255 (2008)
Pardoux, E., Tang, S.: Forward-backward stochastic differential equations and quasilinear parabolic PDEs. Probab. Theory Related Fields 114, 123–150 (1999)
Peng, S., Yang, Z.: Anticipated backward stochastic differential equations. Ann. Probab. 37, 877–902 (2009)
Wang, B., Zhang, J.: Social optima in mean field linear-quadratic-Gaussian models with Markov jump parameters. SIAM J. Control. Optim. 55, 429–456 (2017)
Wang, B., Zhang, H., Zhang, J.: Mean field linear-quadratic control: uniform stabilization and social optimality. Automatica 121, 109088 (2020)
Yong, J., Zhou, X.Y.: Stochastic Controls: Hamiltonian Systems and HJB Equations. Springer-Verlag, New York (1999)
Yu, Z.: The stochastic maximum principle for optimal control problems of delay systems involving continuous and impulse controls. Automatica 48, 2420–2432 (2012)
Zhang, S., Xiong, J., Shi, J.: A linear-quadratic optimal control problem of stochastic differential equations with delay and partial information. Syst. Control Lett. 157, 105046 (2021)
Funding
This work was supported by the National Key R &D Program of China (No. 2022YFA1006104), the National Natural Science Foundation of China (Nos. 12022108, 11971267, 12001320, 12371447, 11831010, 61961160732), the Natural Science Foundation of Shandong Province (Nos. ZR2022JQ01, ZR2019ZD42), the Taishan Scholars Climbing Program of Shandong (No. TSPD20210302), the Taishan Scholars Young Program of Shandong (No. TSQN202211032), the Distinguished Young Scholars Program and the Young Scholars Program of Shandong University.
Author information
Authors and Affiliations
Contributions
All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by TN, SW and ZW. The first draft of the manuscript was written by TN and SW, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of Interests
The authors have no relevant financial or non-financial interests to disclose.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Nie, T., Wang, S. & Wu, Z. Linear-Quadratic Delayed Mean-Field Social Optimization. Appl Math Optim 89, 4 (2024). https://doi.org/10.1007/s00245-023-10067-5
Accepted:
Published:
DOI: https://doi.org/10.1007/s00245-023-10067-5