Robust Model Checking with Imprecise Markov Reward Models
Alberto Termine,
Alessandro Antonucci,
Alessandro Facchini
et al.
Abstract:Because of the widespread diffusion of computational systems of stochastic nature, in recent years probabilistic model checking has become an important area of research. However, despite its great success, standard probabilistic model checking suffers the limitation of requiring a sharp specification of the probabilities governing the model behaviour. Imprecise probability theory offers a natural approach to overcome such limitation by a sensitivity analysis with respect to the values of these parameters. Howe… Show more
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