Stochastic Bounds for Partially generated Markov chains: an algebraic approach
Résumé
We propose several algorithms to obtain bounds based on Censored Markov Chains to analyze partially generated discrete time Markov chains. The main idea is to avoid the generation of a huge (or even infinite) state space and to truncate the state space during the visit. The approach is purely algebraic and provides element-wise and stochastic bounds for the CMC.