This article is concerned with linear quadratic optimal control problems of mean-field stochastic differential equations (MF-SDE) with deterministic coefficients. To treat the time inconsistency of the optimal control problems, linear closed-loop equilibrium strategies are introduced and characterized by variational approach. Our developed methodology drops the delicate convergence procedures in Yong [Trans. Amer. Math. Soc. 369 (2017) 5467–5523]. When the MF-SDE reduces to SDE, our Riccati system coincides with the analogue in Yong [Trans. Amer. Math. Soc. 369 (2017) 5467–5523]. However, these two systems are in general different from each other due to the conditional mean-field terms in the MF-SDE. Eventually, the comparisons with pre-committed optimal strategies, open-loop equilibrium strategies are given in details.
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DOI : 10.1051/cocv/2019057
Mots-clés : Mean-field linear-quadratic optimal control problems, time inconsistency, closed-loop equilibrium strategies, Riccati system
@article{COCV_2020__26_1_A41_0, author = {Wang, Tianxiao}, title = {On closed-loop equilibrium strategies for mean-field stochastic linear quadratic problems}, journal = {ESAIM: Control, Optimisation and Calculus of Variations}, publisher = {EDP-Sciences}, volume = {26}, year = {2020}, doi = {10.1051/cocv/2019057}, mrnumber = {4117803}, zbl = {1442.93048}, language = {en}, url = {http://www.numdam.org/articles/10.1051/cocv/2019057/} }
TY - JOUR AU - Wang, Tianxiao TI - On closed-loop equilibrium strategies for mean-field stochastic linear quadratic problems JO - ESAIM: Control, Optimisation and Calculus of Variations PY - 2020 VL - 26 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/cocv/2019057/ DO - 10.1051/cocv/2019057 LA - en ID - COCV_2020__26_1_A41_0 ER -
%0 Journal Article %A Wang, Tianxiao %T On closed-loop equilibrium strategies for mean-field stochastic linear quadratic problems %J ESAIM: Control, Optimisation and Calculus of Variations %D 2020 %V 26 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/cocv/2019057/ %R 10.1051/cocv/2019057 %G en %F COCV_2020__26_1_A41_0
Wang, Tianxiao. On closed-loop equilibrium strategies for mean-field stochastic linear quadratic problems. ESAIM: Control, Optimisation and Calculus of Variations, Tome 26 (2020), article no. 41. doi : 10.1051/cocv/2019057. http://www.numdam.org/articles/10.1051/cocv/2019057/
[1] A maximum principle for SDEs of mean-field type. Appl. Math. Optim. 63 (2011) 341–356. | DOI | MR | Zbl
and ,[2] Linear quadratic optimal stochastic control with random coefficients. SIAM J. Control Optim. 14 (1976) 419–444. | DOI | MR | Zbl
,[3] On time-inconsistent stochastic control in continuous time. Finance Stoch. 21 (2017) 331–360. | DOI | MR | Zbl
, and ,[4] Mean-field backward stochastic differential equations: a limit approach. Ann. Probab. 37 (2009) 1524–1565. | DOI | MR | Zbl
, , and ,[5] A general maximum principle for SDEs of mean-field type. Appl. Math. Optim. 64 (2011) 197–216. | DOI | MR | Zbl
, and ,[6] Mean-field stochastic differential equations and associated PDEs. Ann. Probab. 45 (2017) 824–878. | DOI | MR | Zbl
, , and ,[7] Control of McKean-Vlasov versus mean field games. Math. Fin. Econ. 7 (2013) 131–166. | DOI | MR | Zbl
, and ,[8] Stochastic linear quadratic regulators with indefinite control weight costs. SIAM J. Control Optim. 36 (1998) 1685–1702. | DOI | MR | Zbl
, and ,[9] Critical dynamics and fluctuations for a mean-field model of cooperative behavior. J. Statist. Phys. 31 (1983) 29–85. | DOI | MR
,[10] Time-inconsistent stochastic linear-quadratic control. SIAM J. Control Optim. 50 (2012) 1548–1572. | DOI | MR | Zbl
, and ,[11] Time-inconsistent stochastic linear-quadratic control: characterization and uniqueness of equilibrium. SIAM J. Control Optim. 55 (2017) 1261–1279. | DOI | MR | Zbl
, and ,[12] Large population stochastic dynamic games: closed-loop McKean-Vlasov systems and the Nash certainty equivalence principle. Commun. Inf. Syst. 6 (2006) 221–252. | DOI | MR | Zbl
, and ,[13] Foundations of kinetic theory, in Proceedings of the 3rd Berkeley symposium on mathematical statistics and probability, Vol. 3 University of California Press, California (1956) 171–197. | MR | Zbl
,[14] Mean-field stochastic linear quadratic optimal control problems: closed-loop solvability. Prob. Uncer. Quan Risk 1 (2016) 2. | DOI | MR | Zbl
, and ,[15] A class of Markov processes associated with nonlinear parabolic equations. Proc. Natl. Acad. Sci. USA 56 (1966) 1907–1911. | DOI | MR | Zbl
,[16] A mean-field stochastic maximum principle via Malliavin calculus. Stochastics 84 (2012) 643–666. | DOI | MR | Zbl
, and ,[17] General linear quadratic optimal stochastic control problems with random coefficients: linear stochastic Hamilton systems and backward stochastic Riccati equations. SIAM J. Control Optim. 42 (2003) 53–75. | DOI | MR | Zbl
,[18] Equilibrium controls in time inconsistent stochastic linear quadratic problems. Appl. Math. Optim. 81 (2020) 591–619. | DOI | MR | Zbl
,[19] Characterizations of equilibrium controls in time inconsistent mean-field stochastic linear quadratic problems. I. Math. Control Relat. Field 9 (2019) 385–409. | DOI | MR | Zbl
,[20] On a matrix Riccati equation of stochastic control. SIAM J. Control 6 (1968) 681–697. | DOI | MR | Zbl
,[21] Time-inconsistent recursive stochastic optimal control problems. SIAM J. Control Optim. 55 (2017) 4156–4201. | DOI | MR | Zbl
, and ,[22] Time-inconsistent optimal control problem and the equilibrium HJB equation. Math. Control Related Fields 2 (2012) 271–329. | DOI | MR | Zbl
,[23] A linear-quadratic optimal control problem for mean-field stochastic differential equations. SIAM J. Control Optim. 51 (2013) 2809–2838. | DOI | MR | Zbl
,[24] Linear-quadratic optimal control problems for mean-field stochastic differential equations – time-consistent solutions. Trans. Amer. Math. Soc. 369 (2017) 5467–5523. | DOI | MR | Zbl
,[25] Stochastic Controls: Hamiltonian Systems and HJB Equations. Springer-Verlag, New York (1999). | DOI | MR | Zbl
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This work is supported in part by NSF of China (Grant 11401404, 11471231, 11231007) and the Fundamental Research Funds for the central Universities (YJ201605).