Correct approximation of stationary distributions LNCS Meggendorfer, Tobias ; https://orcid.org/0000-0002-1712-2165 ddc:000 A classical problem for Markov chains is determining their stationary (or steady-state) distribution. This problem has an equally classical solution based on eigenvectors and linear equation systems. However, this approach does not scale to large instances, and iterative solutions are desirable. It turns out that a naive approach, as used by current model checkers, may yield completely wrong results. We present a new approach, which utilizes recent advances in partial exploration and mean payoff computation to obtain a correct, converging approximation. Springer Nature 2023 info:eu-repo/semantics/conferenceObject doc-type:conferenceObject text http://purl.org/coar/resource_type/c_5794 https://research-explorer.ista.ac.at/record/13139 https://research-explorer.ista.ac.at/download/13139/13148 Meggendorfer T. Correct approximation of stationary distributions. In: <i>TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems</i>. Vol 13993. Springer Nature; 2023:489-507. doi:<a href="https://doi.org/10.1007/978-3-031-30823-9_25">10.1007/978-3-031-30823-9_25</a> eng info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-031-30823-9_25 info:eu-repo/semantics/altIdentifier/issn/0302-9743 info:eu-repo/semantics/altIdentifier/e-issn/1611-3349 info:eu-repo/semantics/altIdentifier/isbn/9783031308222 info:eu-repo/semantics/altIdentifier/wos/001288688000025 info:eu-repo/semantics/altIdentifier/arxiv/2301.08137 https://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess