A Sample-Wise Data Driven Control Solver for the Stochastic Optimal Control Problem with Unknown Model Parameters (Communications in Computational Physics, 2023)
In this work, an efficient sample-wise data driven control solver will be developed to solve the stochastic optimal control problem with unknown model parameters. A direct filter method will be applied as an online parameter estimation methodthat dynamically estimates the target model parameters upon receiving the data, anda sample-wise optimal control solver will be provided to efficiently search for the optimal control. Then, an effective overarching algorithm will be introduced to combinethe parameter estimator and the optimal control solver. Numerical experiments willbe carried out to demonstrate the effectiveness and the efficiency of the sample-wisedata driven control method.
Keywords: Stochastic optimal control; parameter estimation; optimal filter; backward stochastic differential equations; stochastic gradient descent.