Probabilistic error analysis for some approximation schemes to optimal control problems
We introduce a class of numerical schemes for optimal stochastic control problems based on a novel Markov chain approximation, which uses, in turn, a piecewise constant policy approximation, Euler–Maruyama time stepping, and a Gauß-Hermite approximation of the Gaußian increments. We provide lower er...
| Autors principals: | , |
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| Format: | Journal article |
| Idioma: | English |
| Publicat: |
Elsevier
2020
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