Weak Dynamic Programming for Generalized State Constraints
Nutz, Marcel; Bouchard, Bruno (2012), Weak Dynamic Programming for Generalized State Constraints, SIAM Journal on Control and Optimization, 50, 6, p. 3344-3373. http://dx.doi.org/10.1137/110852942
Type
Article accepté pour publication ou publiéDate
2012Journal name
SIAM Journal on Control and OptimizationVolume
50Number
6Publisher
SIAM
Pages
3344-3373
Publication identifier
Metadata
Show full item recordAbstract (EN)
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.Subjects / Keywords
Comparison theorem; Viscosity solution; Hamilton-Jacobi-Bellman equation; Expectation constraint; State constraint; Weak dynamic programmingRelated items
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