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cs.LG2026
A Model-Free Continuous-Time RL Algorithm from Discrete-Time Off-Policy Data with End-to-End Guarantees
Chaorui Yao, Yuming Paul Zhang, Lin Yang +1
In this paper, we study continuous-time reinforcement learning, where the state follows an unknown stochastic differential equation but only a fixed off-policy batch of discrete-ti…
math.OC2026
Discretization error from regularized Reinforcement Learning to continuous-time stochastic control
Huyên Pham, Yuming Paul Zhang, Yuhua Zhu
This paper establishes a rigorous connection between regularized discrete-time reinforcement learning (RL) and continuous-time stochastic optimal control. Specifically, classical R…