Flow faster: efficient decision algorithms for probabilistic simulations

Abstraction techniques based on simulation relations have become an important and effective proof technique to avoid the infamous state space explosion problem. In the context of Markov chains, strong and weak simulation relations have been proposed ((B. Jonsson and K.G. Larsen, 1991), (C. Baier et al., 2002)), together with corresponding decision algorithms ((C. Baier et al., 2000), (C. Baier et al., 2004), but it is as yet unclear whether they can be used as effectively as their non-stochastic counterparts. This paper presents drastically improved algorithms to decide whether one (discrete- or continuous-time) Markov chain strongly or weakly simulates another. The key innovation is the use of parametric maximum flow techniques to amortize computations

Published in:
Tools and Algorithms for the Construction and Analysis of Systems. 13th International Conference, TACAS 2007. Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2007. Proceedings (Lecture Notes in Computer Science Vol. 4424), 155-69
Presented at:
Braga, Portugal

 Record created 2008-05-13, last modified 2020-07-30

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