~Embedding~ and ~modular embedding~ are two well-known techniques for measuring and comparing the expressiveness of languages—sequential and concurrent programming languages, respectively.
The emergence of new classes of computational systems featuring stochastic behaviours — such as pervasive, adaptive, self-organising systems — requires new tools for probabilistic languages.
In this paper, we recall and refine the notion of ~probabilistic modular embedding~ (PME) as an extension to modular embedding meant to capture the expressiveness of stochastic systems, and show its application to different coordination languages providing probabilistic mechanisms for stochastic systems.