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Dynamic Stochastic Optimization

  • J. Frédéric BonnansEmail author
Chapter
Part of the Universitext book series (UTX)

Abstract

Dynamic stochastic optimization problems have the following information constraint: each decision must be a function of the available information at the corresponding time. This can be expressed as a linear constraint involving conditional expectations. This chapter develops the corresponding theory for convex problems with full observation of the state. The resulting optimality system involves a backward costate equation, the control variable being a point of minimum of some Hamiltonian function.

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Inria-Saclay and Centre de Mathématiques AppliquéesÉcole PolytechniquePalaiseauFrance

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