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Date
2011-05-04Type
- Working Paper
ETH Bibliography
yes
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Abstract
We provide a dynamic programming principle for stochastic optimal control problems with expectation constraints. A weak formulation, using test functions and a probabilistic relaxation of the constraint, avoids restrictions related to a measurable selection but still implies the Hamilton-Jacobi-Bellman equation in the viscosity sense. We treat open state constraints as a special case of expectation constraints and prove a comparison theorem to obtain the equation for closed state constraints. Show more
Publication status
publishedExternal links
Journal / series
arXivPages / Article No.
Publisher
Cornell UniversitySubject
Weak dynamic programming; State constraint; Expectation constraint; Hamilton-Jacobi-Bellman equation; Viscosity solution; Comparison theoremOrganisational unit
03844 - Soner, Mete (emeritus) / Soner, Mete (emeritus)
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ETH Bibliography
yes
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