---
res:
  bibo_abstract:
  - 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.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Tobias
      foaf_name: Meggendorfer, Tobias
      foaf_surname: Meggendorfer
      foaf_workInfoHomepage: http://www.librecat.org/personId=b21b0c15-30a2-11eb-80dc-f13ca25802e1
    orcid: 0000-0002-1712-2165
  bibo_doi: 10.1007/978-3-031-30823-9_25
  bibo_volume: 13993
  dct_date: 2023^xs_gYear
  dct_identifier:
  - UT:001288688000025
  dct_isPartOf:
  - http://id.crossref.org/issn/0302-9743
  - http://id.crossref.org/issn/1611-3349
  - http://id.crossref.org/issn/9783031308222
  dct_language: eng
  dct_publisher: Springer Nature@
  dct_title: Correct approximation of stationary distributions@
...