Some insight on the meaning of "modeling power" for Stochastic Petri Net models is given. Extensions characterizing a Stochastic Petri Net are categorized as logical or stochastic. Three logical constructs are shown to be equivalent: inhibitor arcs, transition priorities, and enabling functions associated with the transitions. A direct transformation of Petri Nets with inhibitor arcs into Petri Nets with transition priorities and vice versa is given, determining a bound on the size of equivalent nets in the two models. As a consequence, the higher priority of immediate transitions over timed transitions in the GSPN model is shown to provide the full power of Turing machines
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