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We consider stochastic models in presence of uncertainty, originating from lack of knowledge of parameters or by unpredictable effects of the environment. We focus on population processes, encompassing a large class of systems, from queueing networks to epidemic spreading. We set up a formal framework for imprecise stochastic processes, where some parameters are allowed to vary in time within a given...
We consider the behaviour of sequences of Continuous Time Markov Chains (CTMC) based models of systems of interacting entities, for increasing population levels, in situations when some transitions of the system have rates that are discontinuous functions. This can happen, for instance, in presence of guarded actions. In this setting, standard deterministic approximation results do not apply. However,...
In biological phenomena like osmosis, the rate of flow of water molecules in or out of biological compartments depends on the solute concentration and on other forces, like hydrostatic pressure. A similar example is the passive transport of ions in and out the cell membrane. In this paper, we address the problem of faithfully modelling these kind of phenomena with an adequate process calculus. We...
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