Abstract
In this chapter, we prove a convergence theorem for appropriate notions of noise and information convergence in closed-loop stochastic optimization problems. The main Theorem is based on epi-convergence results, which take into account constraints defined by characteristic functions of sets.
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Notes
- 1.
In order to maintain consistency with all previous chapters, we have interverted the traditional order \(f(\omega ,u)\) of arguments of an integrand.
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© 2015 Springer International Publishing Switzerland
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Carpentier, P., Chancelier, JP., Cohen, G., De Lara, M. (2015). Convergence Issues in Stochastic Optimization. In: Stochastic Multi-Stage Optimization. Probability Theory and Stochastic Modelling, vol 75. Springer, Cham. https://doi.org/10.1007/978-3-319-18138-7_8
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DOI: https://doi.org/10.1007/978-3-319-18138-7_8
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-18137-0
Online ISBN: 978-3-319-18138-7
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