A stochastic automata model and its algebraic approach

We discuss a new model for the analysis and simulation of stochastic systems which we call stochastic automata. Basically, they are a combination of the timed automata model and generalised semi-markovian processes (GSMPs for short). We discuss their behaviour and we compare them to the GSMPs model. In addition, we define a stochastic process algebra that supports general distribution (both continuous and discrete). Its semantics is given in terms of stochastic automata. We show that stochastic automata can be expressed in terms of the process algebra. We discuss a concrete example and we finish by discussing our current work on the topic and possible future directions.