Visualizing generalized semi-Markov processes
Lee W. Schruben, Eric L. Savage · 1996
Generalized Semi-Markov Processes (GSMPs) are usually described by sets of variables, events and clock distributions. This kind of representation often lacks intuitive appeal. In this paper we propose a mapping from GSMPs to Event Graph Models. This mapping allows us to use an event graph to visualize a GSMP model as an intermediate step to implemcniation. By examining the event graph model, we can perform logic checking and verification more easily than if we try to interpret the GSMP description.