A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound

20 Nov 2019Gal DalalBalazs SzorenyiGugan Thoppe

Policy evaluation in reinforcement learning is often conducted using two-timescale stochastic approximation, which results in various gradient temporal difference methods such as GTD(0), GTD2, and TDC. Here, we provide convergence rate bounds for this suite of algorithms... (read more)

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