Randomized Algorithm: A viability computation

We deal with the problem of computing maximal viability sets for nonlinear continuous or hybrid systems. Our main objective is to beat the curse of dimensionality, that is, we wan to avoid the exponential growth of required computational resource with respect to the dimension of the system. We propose a randomized approach for viability computation: we avoid griding the state-space, and use random extraction of points instead. This algorithm was implemented successfully to linear and nonlinear examples. We provide comparison of our results with results of other method.