Mean-Field stochastic Linear Quadratic optimal control problems: Open-loop solvabilities
ESAIM: Control, Optimisation and Calculus of Variations, Tome 23 (2017) no. 3, pp. 1099-1127.

This paper is concerned with a mean-field linear quadratic (LQ, for short) optimal control problem with deterministic coefficients. It is shown that convexity of the cost functional is necessary for the finiteness of the mean-field LQ problem, whereas uniform convexity of the cost functional is sufficient for the open-loop solvability of the problem. By considering a family of uniformly convex cost functionals, a characterization of the finiteness of the problem is derived and a minimizing sequence, whose convergence is equivalent to the open-loop solvability of the problem, is constructed. Then, it is proved that the uniform convexity of the cost functional is equivalent to the solvability of two coupled differential Riccati equations and the unique open-loop optimal control admits a state feedback representation in the case that the cost functional is uniformly convex. Finally, some examples are presented to illustrate the theory developed.

Reçu le :
Accepté le :
DOI : 10.1051/cocv/2016023
Classification : 49N10, 49N35, 93E20
Mots clés : Mean-field stochastic differential equation, linear quadratic optimal control, Riccati equation, finiteness, open-loop solvability, feedback representation
Sun, Jingrui 1

1 Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, P.R. China.
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     title = {Mean-Field stochastic {Linear} {Quadratic} optimal control problems: {Open-loop} solvabilities},
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Sun, Jingrui. Mean-Field stochastic Linear Quadratic optimal control problems: Open-loop solvabilities. ESAIM: Control, Optimisation and Calculus of Variations, Tome 23 (2017) no. 3, pp. 1099-1127. doi : 10.1051/cocv/2016023. http://archive.numdam.org/articles/10.1051/cocv/2016023/

N.U. Ahmed, Nonlinear diffusion governed by McKean−Vlasov equation on Hilbert space and optimal control. SIAM J. Control Optim. 46 (2007) 356–378. | DOI | MR | Zbl

N.U. Ahmed and X. Ding, A semilinear McKean−Vlasov stochastic evolution equation in Hilbert space. Stoch. Proc. Appl. 60 (1995) 65–85. | DOI | MR | Zbl

N.U. Ahmed and X. Ding, Controlled McKean−Vlasov equations. Commun. Appl. Anal. 5 (2001) 183–206. | MR | Zbl

D. Andersson and B. Djehiche, A maximum principle for SDEs of mean-field type. Appl. Math. Optim. 63 (2011) 341–356. | DOI | MR | Zbl

V.S. Borkar and K.S. Kumar, McKean−Vlasov limit in portfolio optimization. Stoch. Anal. Appl. 28 (2010) 884–906. | DOI | MR | Zbl

R. Buckdahn, B. Djehiche and J. Li, A general maximum principle for SDEs of mean-field type. Appl. Math. Optim. 64 (2011) 197–216. | DOI | MR | Zbl

R. Buckdahn, B. Djehiche, J. Li and S. Peng, Mean-field backward stochastic differential equations: A limit approach. Ann. Probab. 37 (2009) 1524–1565. | DOI | MR | Zbl

R. Buckdahn, J. Li and S. Peng, Mean-field backward stochastic differential equations and related partial differential equations. Stoch. Process. Appl. 119 (2009) 3133–3154. | DOI | MR | Zbl

T. Chan, Dynamics of the McKean−Vlasov equation. Ann. Probab. 22 (1994) 431–441. | DOI | MR | Zbl

T. Chiang, McKean−Vlasov equations with discontinuous coefficients. Soochow J. Math. 20 (1994) 507–526. | MR | Zbl

D. Crisan and J. Xiong, Approximate McKean−Vlasov representations for a class of SPDEs. Stochastics 82 (2010) 53–68. | DOI | MR | Zbl

D.A. Dawson, Critical dynamics and fluctuations for a mean-field model of cooperative behavior. J. Statist. Phys. 31 (1983) 29–85. | DOI | MR

D.A. Dawson and J. Gärtner, Large deviations from the McKean−Vlasov limit for weakly interacting diffusions. Stochastics 20 (1987) 247–308. | DOI | MR | Zbl

J. Gärtner, On the McKean−Vlasov limit for interacting diffusions. Math. Nachr. 137 (1988) 197–248. | DOI | MR | Zbl

C. Graham, McKean−Vlasov Ito-Skorohod equations, and nonlinear diffusions with discrete jump sets. Stoch. Proc. Appl. 40 (1992) 69–82. | DOI | MR | Zbl

J. Huang, X. Li, and J. Yong, A linear-quadratic optimal control problem for mean-field stochastic differential equations in infinite horizon. Math. Control Relat. Fields 5 (2015) 97–139. | DOI | MR | Zbl

M. Huang, R.P. Malhamé, and P.E. Caines, Large population stochastic dynamic games: Closed-loop McKean−Vlasov systems and the Nash certainty equivalence principle. Commun. Inf. Syst. 6 (2006) 221–251. | DOI | MR | Zbl

M. Kac, Foundations of kinetic theory. Proc. of 3rd Berkeley Sympos. Math. Statist. Prob. 3 (1956) 171–197. | MR | Zbl

P.M. Kotelenez and T.G. Kurtz, Macroscopic limit for stochastic partial differential equations of McKean−Vlasov type. Prob. Theory Relat. Fields 146 (2010) 189–222. | DOI | MR | Zbl

N. I. Mahmudov and M.A. Mckibben, On a class of backward McKean−Vlasov stochastic equations in Hilbert space: Existence and convergence properties. Dynam. Syst. Appl. 16 (2007) 643–664. | MR | Zbl

H.P. Mckean, A class of Markov processes associated with nonlinear parabolic equations. Proc. Natl. Acad. Sci. USA 56 (1966) 1907–1911. | DOI | MR | Zbl

T. Meyer-Brandis, B. Øksendal and X. Y. Zhou, A mean-field stochastic maximum principle via Malliavin calculus. Stochastics 84 (2012) 643–666. | DOI | MR | Zbl

J.Y. Park, P. Balasubramaniam and Y.H. Kang, Controllability of McKean−Vlasov stochastic integrodifferential evolution equation in Hilbert spaces. Numer. Funct. Anal. Optim. 29 (2008) 1328–1346. | DOI | MR | Zbl

M. Scheutzow, Uniqueness and non-uniqueness of solutions of Vlasov-McKean equations. J. Austral. Math. Soc., Ser. A 43 (1987) 246–256. | DOI | MR | Zbl

J. Sun and J. Yong, Linear Quadratic Stochastic Differential Games: Open-Loop and Closed-Loop Saddle Points. SIAM J. Control Optim. 52 (2014) 4082–4121. | DOI | MR | Zbl

J. Sun, X. Li and J. Yong, Open-Loop and Closed-Loop Solvabilities for Stochastic Linear Quadratic Optimal Control Problems. SIAM J. Control Optim. 54 (2016) 2274–2308. | DOI | MR | Zbl

A. Yu. Veretennikov, On ergodic measures for McKean−Vlasov stochastic equations, in Monte Carlo and quasi-Monte Carlo methods 2004. Springer, Berlin (2006) 471–486. | MR | Zbl

J. Yong, Linear-Quadratic Optimal Control Problems for Mean-Field Stochastic Differential Equations. SIAM J. Control Optim. 51 (2013) 2809–2838. | DOI | MR | Zbl

J. Yong and X.Y. Zhou, Stochastic Controls: Hamiltonian Systems and HJB Equations. Springer-Verlag, New York (1999). | MR | Zbl

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