On Probabilistic Automata in Continuous Time

Christian Eisentraut, Holger Hermanns, Lijun Zhang

    Research output: Contribution to journalConference articleResearchpeer-review


    We develop a compositional behavioural model that integrates a variation of probabilistic automata into a conservative extension of interactive Markov chains. The model is rich enough to embody the semantics of generalised stochastic Petri nets. We define strong and weak bisimulations and discuss their compositionality properties. Weak bisimulation is partly oblivious to the probabilistic branching structure, in order to reflect some natural equalities in this spectrum of models. As a result, the standard way to associate a stochastic process to a generalised stochastic Petri net can be proven sound with respect to weak bisimulation.
    Original languageEnglish
    JournalSymposium on Logic in Computer Science
    Pages (from-to)342 - 351
    Publication statusPublished - 2010
    Event25th Annual IEEE Symposium on Logic in Computer Science - Edinburgh, United Kingdom
    Duration: 11 Jul 201014 Jul 2010
    Conference number: 25


    Conference25th Annual IEEE Symposium on Logic in Computer Science
    Country/TerritoryUnited Kingdom
    Internet address


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