Abstract
We present the first sufficient conditions that guarantee stability of two-timescale stochastic approximation schemes. Our analysis is based on the ordinary differential equation (ODE) method and is an extension of the results in Borkar and Meyn (2000) for single-timescale schemes. As an application of our result, we show the stability of iterates in a two-timescale stochastic approximation scheme arising in reinforcement learning.
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