Vietnam Journal of Mathematics

, Volume 42, Issue 1, pp 83–113 | Cite as

Solving Stochastic Optimal Control Problems by a Wiener Chaos Approach

  • Tony HuschtoEmail author
  • Sebastian Sager


We introduce a novel generic methodology to solve continuous finite-horizon stochastic optimal control problems (SOCPs). We treat controlled stochastic differential equations (SDEs) within the Wiener chaos framework by utilizing Malliavin calculus and developing innovative ideas to preserve the feedback character of optimal Markov decision rules.

This allows a direct reformulation of SOCPs into deterministic ones. Hence, it facilitates using Bock’s direct multiple shooting method for solving SOCPs and pioneers the extension of sophisticated methods for deterministic control to the broad context of SDEs.

Numerical examples validate this new framework with huge computational advantages compared to standard ideas in SOC.


Stochastic optimal control Markov control Wiener chaos Malliavin calculus Direct multiple shooting 

Mathematics Subject Classification (2000)

93E20 60H35 49J15 



The authors like to express their gratitude to Prof. M. Podolskij from the University of Heidelberg for his helpful comments and suggestions.

This research was supported by the Heidelberg Graduate School Mathematical and Computational Methods for the Sciences and by the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement n o  FP7-ICT-2009-4 248940.


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Copyright information

© Vietnam Academy of Science and Technology (VAST) and Springer Science+Business Media Singapore 2014

Authors and Affiliations

  1. 1.Interdisciplinary Center for Scientific ComputingRuprecht-Karls University of HeidelbergHeidelbergGermany
  2. 2.Institute for Mathematical OptimizationOtto-von-Guericke University MagdeburgMagdeburgGermany

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