Authors: Lozovanu Dmitrii, Stefan Pickl
Abstract
New calculation procedures for finding the probabilities of state transitions of the system in Markov chains
based on dynamic programming are developed and polynomial time algorithms for determining the limit state matrix in such
processes are proposed. Computational complexity aspects and possible applications of the proposed algorithms for the
stochastic optimization problems are characterized.
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