Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-41202-8_20
Title: Asymptotic bounds for quantitative verification of perturbed probabilistic systems
Authors: Su, G.
Rosenblum, D.S. 
Issue Date: 2013
Citation: Su, G.,Rosenblum, D.S. (2013). Asymptotic bounds for quantitative verification of perturbed probabilistic systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8144 LNCS : 297-312. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-41202-8_20
Abstract: The majority of existing probabilistic model checking case studies are based on well understood theoretical models and distributions. However, real-life probabilistic systems usually involve distribution parameters whose values are obtained by empirical measurements and thus are subject to small perturbations. In this paper, we consider perturbation analysis of reachability in the parametric models of these systems (i.e., parametric Markov chains) equipped with the norm of absolute distance. Our main contribution is a method to compute the asymptotic bounds in the form of condition numbers for constrained reachability probabilities against perturbations of the distribution parameters of the system. The adequacy of the method is demonstrated through experiments with the Zeroconf protocol and the hopping frog problem. © 2013 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/124983
ISBN: 9783642412011
ISSN: 03029743
DOI: 10.1007/978-3-642-41202-8_20
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