Distribution-Based Bisimulation for Labelled Markov Processes

  • Pengfei Yang
  • David N. Jansen
  • Lijun ZhangEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10419)


In this paper we propose a (sub)distribution-based bisimulation for labelled Markov processes and compare it with earlier definitions of state and event bisimulation, which both only compare states. In contrast to those state-based bisimulations, our distribution bisimulation is weaker, but corresponds more closely to linear properties. We construct a logic and a metric to describe our distribution bisimulation and discuss linearity, continuity and compositional properties.


Labelled Markov Processes (LMPs) Distributed Bisimulations Subdistribution State Bisimulation Discrete Probabilistic Systems 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work has been supported by the National Natural Science Foundation of China (Grants 61532019, 61472473), the CAS/SAFEA International Partnership Program for Creative Research Teams, the Sino-German CDZ project CAP (GZ 1023).


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Authors and Affiliations

  1. 1.State Key Laboratory of Computer ScienceInstitute of Software, CASBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina

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