Analyzing Divergence for Nondeterministic Probabilistic Models
arxiv(2024)
摘要
Branching and weak probabilistic bisimilarities are two well-known notions
capturing behavioral equivalence between nondeterministic probabilistic
systems. For probabilistic systems, divergence is of major concern. Recently
several divergence-sensitive refinements of branching and weak probabilistic
bisimilarities have been proposed in the literature. Both the definitions of
these equivalences and the techniques to investigate them differ significantly.
This paper presents a comprehensive comparative study on divergence-sensitive
behavioral equivalence relations that refine the branching and weak
probabilistic bisimilarities. Additionally, these equivalence relations are
shown to have efficient checking algorithms. The techniques of this paper might
be of independent interest in a more general setting.
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