Markov Chain Concentration with an Application in Reinforcement Learning

01/07/2023

∙

by   Debangshu Banerjee, et al.

∙

0

∙

share

Given X_1,· ,X_N random variables whose joint distribution is given as μ 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