We discuss the evolution scenarios for hybrid systems described by families of parameters changing in time. The systems are in discrete states and the transitions between states are probabilistic. The need for such scenarios arises in applications. In particular, in medicine such scenarions can be viewed as patient histories and can be used in medical training and testing.
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