{"quality_controlled":"1","date_published":"2023-04-22T00:00:00Z","volume":13993,"scopus_import":"1","ddc":["000"],"publication_identifier":{"issn":["0302-9743"],"eissn":["1611-3349"],"isbn":["9783031308222"]},"article_processing_charge":"No","related_material":{"record":[{"id":"14990","status":"public","relation":"research_data"}]},"intvolume":" 13993","title":"Correct approximation of stationary distributions","citation":{"short":"T. Meggendorfer, in:, TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems, Springer Nature, 2023, pp. 489–507.","ama":"Meggendorfer T. Correct approximation of stationary distributions. In: TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems. Vol 13993. Springer Nature; 2023:489-507. doi:10.1007/978-3-031-30823-9_25","apa":"Meggendorfer, T. (2023). Correct approximation of stationary distributions. In TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems (Vol. 13993, pp. 489–507). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-30823-9_25","chicago":"Meggendorfer, Tobias. “Correct Approximation of Stationary Distributions.” In TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems, 13993:489–507. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30823-9_25.","ieee":"T. Meggendorfer, “Correct approximation of stationary distributions,” in TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems, Paris, France, 2023, vol. 13993, pp. 489–507.","ista":"Meggendorfer T. 2023. Correct approximation of stationary distributions. TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems. TACAS: Tools and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13993, 489–507.","mla":"Meggendorfer, Tobias. “Correct Approximation of Stationary Distributions.” TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems, vol. 13993, Springer Nature, 2023, pp. 489–507, doi:10.1007/978-3-031-30823-9_25."},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"has_accepted_license":"1","day":"22","language":[{"iso":"eng"}],"author":[{"full_name":"Meggendorfer, Tobias","id":"b21b0c15-30a2-11eb-80dc-f13ca25802e1","first_name":"Tobias","last_name":"Meggendorfer","orcid":"0000-0002-1712-2165"}],"page":"489-507","year":"2023","oa":1,"abstract":[{"text":"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.","lang":"eng"}],"conference":{"end_date":"2023-04-27","location":"Paris, France","start_date":"2023-04-22","name":"TACAS: Tools and Algorithms for the Construction and Analysis of Systems"},"status":"public","file":[{"date_created":"2023-06-19T07:18:40Z","file_size":521951,"creator":"dernst","access_level":"open_access","success":1,"date_updated":"2023-06-19T07:18:40Z","relation":"main_file","file_id":"13148","content_type":"application/pdf","checksum":"59f707a3949c03793251b0d04c62542a","file_name":"2023_LNCS_Meggendorfer.pdf"}],"_id":"13139","file_date_updated":"2023-06-19T07:18:40Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2024-02-27T07:19:33Z","type":"conference","doi":"10.1007/978-3-031-30823-9_25","department":[{"_id":"KrCh"}],"oa_version":"Published Version","publication":"TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems","publication_status":"published","alternative_title":["LNCS"],"date_created":"2023-06-18T22:00:46Z","month":"04","external_id":{"arxiv":["2301.08137"]},"publisher":"Springer Nature"}