Stochastic continuous-state approximation of Markovian Petri net systems

Fluidification constitutes a relaxation technique to study discrete event systems through a continuous approximated model, thus avoiding the state explosion problem. In this paper, the approximation by Timed Continuous Petri nets under infinite server semantics is studied. The main contribution of this work is the addition of gaussian noise in order to obtain a better (but stochastic) approximation when synchronizations are important.