TY - CONF
AB - 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.
AU - Meggendorfer, Tobias
ID - 13139
SN - 0302-9743
T2 - TACAS 2023: Tools and Algorithms for the Construction and Analysis of Systems
TI - Correct approximation of stationary distributions
VL - 13993
ER -