Learn 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)
We present a novel approach to learn the formulae characterising the emergent behaviour of a dynamical system from system observations. At a high level, the approach starts by devising a statistical dynamical model of the system which optimally fits the observations. We then propose general optimisation strategies for selecting high support formulae (under(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)
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)
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)
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)
Continuous time Markov Chains (CTMCs) are a convenient mathematical model for a broad range of natural and computer systems. As a result, they have received considerable attention in the theoretical computer science community, with many important techniques such as model checking being now mainstream. However, most methodolo-gies start with an assumption of(More)