On the Approximation of Stochastic Concurrent Constraint Programming by Master Equation

On the Approximation of Stochastic Concurrent Constraint Programming by Master Equation

We explore the relation between the stochastic semantic associated to stochastic Concurrent Constrain Programming (sCCP) and its fluid-flow approximation. Writing the master equation for a sCCP model, we can show that the fluid flow equation is a first-order approximation of the true equation for the average. Moreover, we introduce a second-order correction and first-order equations for the var...

Stochastic Concurrent Constraint Programming

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 version, and a connection between the t...

Hybrid approximation of stochastic concurrent constraint programs

Modeling in computational systems biology is dominated by two formalisms, the first one being (mainly ordinary) differential equations and the second one being continuous-time stochastic processes [1, 2]. Both methodologies have their roots reaching back to physical and chemical arguments that, at least for modeling biochemical reactions, give strong foundations to the approach. Recently, stoch...

Stochastic Concurrent Constraint Programming and Differential Equations

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 inverse procedure translating ODE’s into sC...

Concurrent Constraint Programming Based on Functional Programming