Second-Order Necessary Conditions for Stochastic Optimal Control Problems

The main purpose of this paper is to present some of our recent results about the secondorder necessary conditions for stochastic optimal controls with the control variable entering into both the drift and the diffusion terms. In particular, when the control region is convex, a pointwise second-orde...

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Veröffentlicht in:SIAM review 2018-03, Vol.60 (1), p.139-178
Hauptverfasser: Zhang, Haisen, Zhang, Xu
Format: Artikel
Sprache:eng
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Zusammenfassung:The main purpose of this paper is to present some of our recent results about the secondorder necessary conditions for stochastic optimal controls with the control variable entering into both the drift and the diffusion terms. In particular, when the control region is convex, a pointwise second-order necessary condition for stochastic singular optimal controls in the classical sense is established, whereas when the control region is allowed to be nonconvex, we obtain a pointwise second-order necessary condition for stochastic singular optimal controls in the sense of the Pontryagin-type maximum principle. Unlike deterministic optimal control problems or stochastic optimal control problems with control-independent diffusions, there exist some essential difficulties in deriving the pointwise second-order necessary optimality conditions from the integral conditions when the controls act in the diffusion terms of the stochastic control systems. Some techniques from Malliavin calculus are employed to overcome these difficulties. Moreover, it is found that, in contrast to the first-order necessary conditions, the correction part of the solution to the second-order adjoint equation appears in the pointwise second-order necessary conditions whenever the diffusion term depends on the control variable, even if the control region is convex.
ISSN:0036-1445
1095-7200
DOI:10.1137/17M1148773