Recent development of stochastic optimal control, applications and deep learning methods
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Organizer(s): |
Name:
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Affiliation:
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Country:
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Omar KEBIRI
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BTU Cottbus-Senftenberg
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Germany
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Introduction:
| | Stochastic optimal control has been developing very fast in the recent years. It has the attention of many applications in epidemic, economy, finance, biology and many other fields, especially in the recent researches areas, such as deep and machine learning.
This special session is to present recent developments of stochastic optimal control and their applications in finance, economy and deep learning methods for solving stochastic dynamical systems, such as BSDEs, 2BSDE, Reflected BSDE ... etc.
The main topics are focused on, but are not limited to:
-1- Stochastic Optimal Control in Mathematical Finance
-2- Machine learning methods for solving control problems
-3- Optimal insurance strategy
-4- Stochastic maximum principle
-5- Uncertainty quantification models and their numerical analysis.
-6- Stochastic homogenization.
-8- Fractional, sub-fractional and multi-fractional stochastic differential equations and their applications.
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