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arXiv · 2301.02926

Markov Chain Concentration with an Application in Reinforcement Learning

Debangshu Banerjee
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Abstract

Given $X_1,\cdot ,X_N$ random variables whose joint distribution is given as $\mu$ we will use the Martingale Method to show any Lipshitz Function $f$ over these random variables is subgaussian. The Variance parameter however can have a simple expression under certain conditions. For example under the assumption that the random variables follow a Markov Chain and that the function is Lipschitz under a Weighted Hamming Metric. We shall conclude with certain well known techniques from concentration of suprema of random processes with applications in Reinforcement Learning

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Debangshu Banerjee. 2023-01-07. Markov Chain Concentration with an Application in Reinforcement Learning. https://arxiv.org/abs/2301.02926

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