Derived rates of order up to n^{-1/6} log^4(n S A) for the high-dimensional CLT of averaged asynchronous Q-learning iterates, plus a general martingale-difference CLT.
Randomized linear programming solves the markov decision problem in nearly linear (sometimes sublinear) time.Mathematics of Operations Research, 45(2):517–546, 2020
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Gaussian Approximation for Asynchronous Q-learning
Derived rates of order up to n^{-1/6} log^4(n S A) for the high-dimensional CLT of averaged asynchronous Q-learning iterates, plus a general martingale-difference CLT.