Finite state machines can be used to model which of the following?

Finite state machines (FSMs) are particularly effective in modeling discrete dynamic systems that have a finite number of states. This means that FSMs can represent systems where the state is defined by a limited set of conditions or configurations, allowing for a clear depiction of how the system transitions from one state to another based on particular inputs or events.

The essence of a finite state machine lies in its ability to transition between these well-defined finite states based on specific triggered actions or signals, making it suitable for applications such as digital logic design, software state management, and various control systems.

When evaluating the other options, it's clear that finite state machines are not appropriate for systems with an infinite number of states, as the term 'finite' inherently indicates that the number of states is limited. Similarly, FSMs are ill-suited for systems that are always static, as one of the fundamental characteristics of an FSM is its capacity to represent dynamic behavior through state changes. Lastly, systems that don't transition would not utilize the FSM framework effectively, because the essence of an FSM is to model the transitions between states, which implies some degree of dynamism.

In summary, the correct choice aligns with the core principles of finite state machines and their purpose in modeling systems that exhibit