Dual Ensemble Kalman Filter for Stochastic Optimal Control
Fuente:
arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866916455602192384 |
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| author | Joshi, Anant A. Taghvaei, Amirhossein Mehta, Prashant G. Meyn, Sean P. |
| author_facet | Joshi, Anant A. Taghvaei, Amirhossein Mehta, Prashant G. Meyn, Sean P. |
| contents | In this paper, stochastic optimal control problems in continuous time and space are considered. In recent years, such problems have received renewed attention from the lens of reinforcement learning (RL) which is also one of our motivation. The main contribution is a simulation-based algorithm -- dual ensemble Kalman filter (EnKF) -- to numerically approximate the solution of these problems. The paper extends our previous work where the dual EnKF was applied in deterministic settings of the problem. The theoretical results and algorithms are illustrated with numerical experiments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_06696 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Dual Ensemble Kalman Filter for Stochastic Optimal Control Joshi, Anant A. Taghvaei, Amirhossein Mehta, Prashant G. Meyn, Sean P. Systems and Control In this paper, stochastic optimal control problems in continuous time and space are considered. In recent years, such problems have received renewed attention from the lens of reinforcement learning (RL) which is also one of our motivation. The main contribution is a simulation-based algorithm -- dual ensemble Kalman filter (EnKF) -- to numerically approximate the solution of these problems. The paper extends our previous work where the dual EnKF was applied in deterministic settings of the problem. The theoretical results and algorithms are illustrated with numerical experiments. |
| title | Dual Ensemble Kalman Filter for Stochastic Optimal Control |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2404.06696 |