Forward and Backward Mean-Field Stochastic Partial Differential Equation and Optimal Control

Maoning Tang , Qingxin Meng , Meijiao Wang

Chinese Annals of Mathematics, Series B ›› 2019, Vol. 40 ›› Issue (4) : 515 -540.

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Chinese Annals of Mathematics, Series B ›› 2019, Vol. 40 ›› Issue (4) : 515 -540. DOI: 10.1007/s11401-019-0149-1
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Forward and Backward Mean-Field Stochastic Partial Differential Equation and Optimal Control

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Abstract

This paper is mainly concerned with the solutions to both forward and backward mean-field stochastic partial differential equation and the corresponding optimal control problem for mean-field stochastic partial differential equation. The authors first prove the continuous dependence theorems of forward and backward mean-field stochastic partial differential equations and show the existence and uniqueness of solutions to them. Then they establish necessary and sufficient optimality conditions of the control problem in the form of Pontryagin’s maximum principles. To illustrate the theoretical results, the authors apply stochastic maximum principles to study the infinite-dimensional linear-quadratic control problem of mean-field type. Further, an application to a Cauchy problem for a controlled stochastic linear PDE of mean-field type is studied.

Keywords

Mean-field / Stochastic partial differential equation / Backward stochastic partial differential equation / Optimal control / Maximum principle / Adjoint equation

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Maoning Tang,Qingxin Meng,Meijiao Wang. Forward and Backward Mean-Field Stochastic Partial Differential Equation and Optimal Control. Chinese Annals of Mathematics, Series B, 2019, 40(4): 515-540 DOI:10.1007/s11401-019-0149-1

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References

[1]

Andersson D, Djehiche B. A maximum principle for SDEs of mean-field type. Applied Mathematics and Optimization, 2011, 63: 341-356

[2]

Bensoussan, A., Lectures on Stochastic Control, Nonlinear Filtering and Stochastic Control, S.K. Mitter, A. Moro (eds.), Springer Lecture Notes in Mathematics, 972, Springer-Verlag, Berlin, 1982.

[3]

Buckdahn R, Djehiche B, Li J, Peng S. Mean-field backward stochastic differential equations: A limit approach. The Annals of Probability, 2009, 37: 1524-1565

[4]

Buckdahn R, Djehiche B, Li J. A general stochastic maximum principle for SDEs of mean-field type. Applied Mathematics and Optimization, 2011, 64: 197-216

[5]

Buckdahn R, Li J, Peng S. Mean-field backward stochastic differential equations and related partial differential equations. Stochastic Processes and Their Applications, 2009, 119: 3133-3154

[6]

Du H, Huang J, Qin Y. A stochastic maximum principle for delayed mean-field stochastic differential equations and its applications. IEEE Transactions on Automatic Control, 2013, 38: 3212-3217

[7]

Du K, Meng Q. A revisit to-theory of super-parabolic backward stochastic partial differential equations in rd. Stochastic Processes and Their Applications, 2010, 120(10): 1996-2015

[8]

Du K, Tang S. Strong solution of backward stochastic partial differential equations in C 2 domains. Probability Theory and Related Fields, 2012, 154(1): 255-285

[9]

Du K, Tang S, Zhang Q. W m,p-solution (p ≥ 2) of linear degenerate backward stochastic partial differential equations in the whole space. Journal of Differential Equations, 2013, 254(7): 2877-2904

[10]

Ekeland I, Temam R. Convex Analysis and Variational Problems, 1976, Amsterdam: North-Holland

[11]

Elliott R, Li X, Ni Y H. Discrete time mean-field stochastic linear-quadratic optimal control problems. Automatica, 2013, 49(11): 3222-3233

[12]

Hu Y, Peng S. Adapted solution of a backward semilinear stochastic evolution equation. Stochastic Analysis and Applications, 1991, 9(4): 445-459

[13]

Kac M. Foundations of kinetic theory. Proceedings of the 3rd Berkeley Symposium on Mathematical Statistics and Probability, 1956, 3: 171-197

[14]

Li J. Stochastic maximum principle in the mean-field controls. Automatica, 2012, 48: 366-373

[15]

McKean H P. A class of Markov processes associated with nonlinear parabolic equations. Proceedings of the National Academy of Sciences, 1966, 56: 1907-1911

[16]

Meng Q, Shen Y. Optimal control of mean-field jump-diffusion systems with delay: A stochastic maximum principle approach. Journal of Computational and Applied Mathematics, 2015, 279: 13-30

[17]

Meyer-Brandis T, Øksendal B, Zhou X Y. A mean-field stochastic maximum principle via Malliavin calculus. Stochastics, 2012, 84: 643-666

[18]

Prévôt C, Rökner M. A concise course on stochastic partial differen-tial equations, 2007, Berlin: Springer-Verlag 1905

[19]

Shen Y, Meng Q, Shi P. Maximum principle for mean-field jump diffusion stochastic delay differential equations and its application to finance. Automatica, 2014, 50(6): 1565-1579

[20]

Shen Y, Siu T K. The maximum principle for a jump-diffusion mean-field model and its application to the mean-variance problem. Nonlinear Analysis: Theory, Methods and Applications, 2013, 86: 58-73

[21]

Wang G, Zhang C, Zhang W. Stochastic maximum principle for mean-field type optimal control under partial information. IEEE Transactions on Automatic Control, 2014, 59(2): 522-528

[22]

Yong J. Linear-quadratic optimal control problems for mean-field stochastic differential equations. SIAM Journal on Control and Optimization, 2013, 51(4): 2809-2838

[23]

Yong J, Zhou X Y. Stochastic Control: Hamiltonian Systems and HJB Equations, 1999, New York: Springer-Verlag

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