Dual Ensemble Kalman Filter for Stochastic Optimal Control
arXiv preprint arXiv:2404.06696, 2024•arxiv.org
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 …
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 …
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.
arxiv.org
Showing the best result for this search. See all results