We propose polynomial-time algorithms to minimise labelled Markov chains whose transition probabilities are not known exactly, have been perturbed, or can only be obtained by sampling. Our algorithms are based on a new notion of an approximate bisimulation quotient, obtained by lumping together states that are exactly bisimilar in a slightly perturbed system. We present experiments that show that our algorithms are able to recover the structure of the bisimulation quotient of the unperturbed system.
翻译:我们建议采用多米时算法,以尽可能减少有标签的Markov链条,这些链条的过渡概率并不完全为人所知,它们已经受到干扰,或者只能通过取样才能获得。 我们的算法基于一种新概念,即一种大约的平衡商数,通过将在一个略为扰动的系统中完全两样相同的国家混在一起获得。 我们提出的实验表明,我们的算法能够恢复无扰动系统的平衡商数结构。