Publication

[EisentrautHKTZ13] Deciding Bisimilarities on Distributions Eisentraut, C.; Hermanns, H.; Krämer, J.; Turrini, A. and Zhang, L. In Quantitative Evaluation of Systems - 10th International Conference (QEST), pages 72-88, Springer, Lecture Notes in Computer Science 8054, 2013.Downloads: pdf, bibURL: http://dx.doi.org/10.1007/978-3-642-40196-1_6 Abstract. Probabilistic automata (PA) are a prominent compositional concurrency model. As a way to justify property-preserving abstractions, in the last years, bisimulation relations over probability distributions have been proposed both in the strong and the weak setting. Different to the usual bisimulation relations, which are defined over states, an algorithmic treatment of these relations is inherently hard, as their carrier set is uncountable, even for finite PAs. The coarsest of these relation, weak distribution bisimulation, stands out from the others in that no equivalent state-based characterisation is known so far. This paper presents an equivalent state-based reformulation for weak distribution bisimulation, rendering it amenable for algorithmic treatment. Then, decision procedures for the probability distribution-based bisimulation relations are presented.