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We present a stochastic version of Concurrent Constraint Programming (CCP), where we associate a rate to each basic instruction that interacts with the constraint store. We give an operational semantic that can be provided either with a discrete or a continuous model of time. The notion of observables is discussed, both for the discrete and the continuous(More)
We tackle the problem of relating models of systems (mainly biological systems) based on stochastic process algebras (SPA) with models based on differential equations. We define a syntactic procedure that translates programs written in stochastic Concurrent Constraint Programming (sCCP) into a set of Ordinary Differential Equations (ODE), and also the(More)
Stochastic models such as Continuous-Time Markov Chains (CTMC) and Stochastic Hybrid Au-tomata (SHA) are powerful formalisms to model and to reason about the dynamics of biological systems, due to their ability to capture the stochasticity inherent in biological processes. A classical question in formal modelling with clear relevance to biological modelling(More)
Hybrid systems are manifest in both the natural and the engineered world, and their complex nature, mixing discrete control and continuous evolution, make it difficult to predict their behaviour. In recent years several process algebras for modelling hybrid systems have appeared in the literature, aimed at addressing this problem. These all assume that(More)
We define a semantics for stochastic Concurrent Constraint Programming (sCCP), a stochastic process algebra, in terms of stochas-tic hybrid automata with piecewise deterministic continuous dynamics. To each program we associate a lattice of hybrid models, parameter-ized with respect to the degree of discreteness left. We study some properties of this(More)
We present an application of stochastic Concurrent Constraint Programming (sCCP) for modeling biological systems. We provide a library of sCCP processes that can be used to describe straightforwardly biological networks. In the meanwhile , we show that sCCP proves to be a general and extensible framework, allowing to describe a wide class of dynamical(More)
In this paper we investigate a potential use of fluid approximation techniques in the context of stochastic model checking of CSL formulae. We focus on properties describing the behaviour of a single agent in a (large) population of agents, exploiting a limit result known also as fast simulation. In particular, we will approximate the behaviour of a single(More)