Abstract
This paper introduces MOCHY, a tool designed for the modeling of concurrent systems with variants of stochastic, timed and hybrid Petri nets. Beyond modeling, the tool serves as a platform for fast simulation, and can be used for statistical verification of properties, controller testing, and learning of control rules. The targeted models are variants of stochastic and timed nets where tokens can be continuous quantities depicting trajectories of moving objects. The architecture of the tool is designed to be as adaptive as possible, and allow the redefinition of objects behaviors or transitions firing through the refinement of a few semantic rules. The framework also allows for the integration of controllers. For any model variant, MOCHY can perform fast simulation, and perform statistical verification, evaluate some quantitative properties of a model, or learn control rules for reachability or quantitative objectives.
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