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A Policy Gradient Framework for Stochastic Optimal Control Problems with Global Convergence Guarantee
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We consider policy gradient methods for stochastic optimal control problem in continuous time. In particular, we analyze the gradient flow for the control, viewed as a continuous time limit of the policy gradient method. We prove the global convergence of the gradient flow and establish a convergence rate under some regularity assumptions. The main novelty in the analysis is the notion of local optimal control function, which is introduced to characterize the local optimality of the iterate.
Forward citations
Cited by 2 Pith papers
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Convergence of Proximal Policy Gradient Method for Problems with Control Dependent Diffusion Coefficients
For linear state dynamics with control-dependent diffusion, proximal policy gradient iterates converge linearly to a stationary control when the running or terminal cost is sufficiently strongly convex.
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