Reinforcement Learning for Continuous Stochastic Control Problems
نویسندگان
چکیده
This paper is concerned with the problem of Reinforcement Learning (RL) for continuous state space and time stocha.stic control problems. We state the Harnilton-Jacobi-Bellman equation satisfied by the value function and use a Finite-Difference method for designing a convergent approximation scheme. Then we propose a RL algorithm based on this scheme and prove its convergence to the optimal solution.
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تاریخ انتشار 1997