These are computed via standard Markov chain solvers (Gauss-Seidel, iterative methods) or simulation for large models.

GSPNs build upon classical Petri nets by dividing transitions into two functional categories:

The profound beauty emerges in the and Inhibitors .

| Formalism | Timing | Use case | |-----------|--------|----------| | Petri nets | No timing | Qualitative (liveness, boundedness) | | SPN | Exponential only | Performance, reliability | | | Exponential + immediate (weights) | Performance + probabilistic decisions | | DSPN | Deterministic + exponential | Real-time systems, timeouts | | Stochastic Process Algebra | Various | Compositional modeling | | Queueing networks | Exponential, some general | Only queueing, no synchronization |

: A finite set of (graphically drawn as circles) representing system states or conditions.