Abstract
The paper provides a precise error estimate for an asymptotic expansion of a certain stochastic control problem related to relative entropy minimization. In particular, it is shown that the expansion error depends on the regularity of functionals on path space. An efficient numerical scheme based on a weak approximation with Monte Carlo simulation is employed to implement the asymptotic expansion in multidimensional settings. Throughout numerical experiments, it is confirmed that the approximation error of the proposed scheme is consistent with the theoretical rate of convergence.
Original language | English |
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Article number | 119 |
Journal | Entropy |
Volume | 26 |
Issue number | 2 |
DOIs | |
State | Published - 2024/02 |
Keywords
- Monte Carlo simulation
- asymptotic expansion
- relative entropy
- stochastic optimization
- weak approximation
ASJC Scopus subject areas
- Information Systems
- Mathematical Physics
- Physics and Astronomy (miscellaneous)
- General Physics and Astronomy
- Electrical and Electronic Engineering