Write . All arguments depend only on this given satisfaction set; they do not require an additional convention for the printed notation . For a state , let . The power set is ordered by set inclusion.
Take and any . By the definition of , we have both and . By transitivity of set inclusion, , so . Since this applies to every member of ,
Thus is an order-preserving function, which is the meaning of monotonicity here. This proof does not need either finiteness or the absence of terminal states.
Let . By computation tree logic semantics, a state belongs to exactly when every infinite path in a transition system starting there stays in at every position, including position zero. There are no terminal states, so every state lies at the start of an infinite path in a transition system.
If , then . For any successor of , every infinite path in a transition system from can be prefixed with . Hence every such continuation stays in , so . Thus and .
Conversely, if , then and every successor belongs to . Every infinite path in a transition system from therefore has its first state in and its entire remaining tail in . Consequently . Both inclusions give
so the desired satisfaction set is a fixed point of .
Every state has at least one successor, so for every . Therefore
The empty set is always a fixed point. Whenever is nonempty, it is therefore an additional, distinct fixed point.
For an explicit example, take a one-state transition system with , the self-loop , and . Then and has the two distinct fixed points and . This example meets the requirement of no terminal states.
The wording does not guarantee distinct additional fixed points for every instance. For example, if , then for every and its only fixed point is . Thus additional fixed points can occur, but need not occur. The universal example is distinct precisely when the desired satisfaction set is nonempty, as also follows from the greatest fixed point argument below.