4.6 Article

Second-Order Necessary Conditions for Stochastic Optimal Control Problems

Journal

SIAM REVIEW
Volume 60, Issue 1, Pages 139-178

Publisher

SIAM PUBLICATIONS
DOI: 10.1137/17M1148773

Keywords

stochastic optimal control; Malliavin calculus; pointwise second-order necessary condition; variational equation; adjoint equation

Funding

  1. NSF of China [11401404, 11471231, 11701470, 11221101, 11231007]
  2. State Scholarship Fund of China Scholarship Council [[2016]3035]
  3. NSFC-CNRS Joint Research Project [11711530142]
  4. PCSIRT [IRT_16R53]
  5. Chang Jiang Scholars Program from the Chinese Education Ministry

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The main purpose of this paper is to present some of our recent results about the second-order 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.

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