A Stochastic Maximum Principle for General Mean-Field Systems

In this paper we study the optimal control problem for a class of general mean-field stochastic differential equations, in which the coefficients depend, nonlinearly, on both the state process as well as of its law. In particular, we assume that the control set is a general open set that is not nece...

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Vydáno v:Applied mathematics & optimization Ročník 74; číslo 3; s. 507 - 534
Hlavní autoři: Buckdahn, Rainer, Li, Juan, Ma, Jin
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.12.2016
Springer Nature B.V
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ISSN:0095-4616, 1432-0606
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Shrnutí:In this paper we study the optimal control problem for a class of general mean-field stochastic differential equations, in which the coefficients depend, nonlinearly, on both the state process as well as of its law. In particular, we assume that the control set is a general open set that is not necessary convex, and the coefficients are only continuous on the control variable without any further regularity or convexity. We validate the approach of Peng (SIAM J Control Optim 2(4):966–979, 1990 ) by considering the second order variational equations and the corresponding second order adjoint process in this setting, and we extend the Stochastic Maximum Principle of Buckdahn et al. (Appl Math Optim 64(2):197–216, 2011 ) to this general case.
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ISSN:0095-4616
1432-0606
DOI:10.1007/s00245-016-9394-9