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 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
Springer US
01.12.2016
Springer Nature B.V |
| Témata: | |
| ISSN: | 0095-4616, 1432-0606 |
| On-line přístup: | Získat plný text |
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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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| Bibliografie: | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0095-4616 1432-0606 |
| DOI: | 10.1007/s00245-016-9394-9 |