For instance, the sequential coupling form is usually driven by a series of discrete uncertain events. The occurrences of uncertain events cause the corresponding state transition, which in turn updates the system units. The reinforcement learning approach provides an uncertainty analysis framework for modeling the knock-on evolution and makes it possible to predict the most probable system state transition sequence from a global perspective. Another uncertainty analysis approach is based on the Boltzmann entropy , which can be adopted to cope with the synchronous coupling form.