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Poisson Equation for Countable Markov Chains: Existence of Solutions and Parameter Dependence by Probabilistic Methods.

机译:可数马氏链的poisson方程:概率方法求解和参数依赖的存在性。

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This paper considers the Poisson equation associated with time- homogeneous Markov chains on a countable state space. The discussion emphasizes probabilistic arguments and focuses on three separate issues, namely (i) the existence and uniqueness of solutions to the Poisson equation, (ii) growth estimates and bounds on these solutions, and (iii) their parametric dependence. Answers to these questions are obtained under a variety of recurrence conditions. Motivating applications can be found in the theory of Markov decision processes in both its adaptive and non-adaptive formulations, and in the theory of Stochastic Approximations. The results complement available results from Potential Theory for Markov chains, and are therefore of independent interest.

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