Transitions between network states determine the state space of the RBN. In classic RBNs, the updating is deterministic and synchronous [15]. Since the number of states of the network is finite and the dynamics are deterministic, sooner or later a state will be repeated in theory (in practice, this can take longer than the age of the universe due to the immense state space). When this occurs, the network has reached an attractor , since the dynamics will remain in that subset of the state space. If the attractor consists of only one state, then it is called a point attractor (similar to a steady state), whereas an attractor consisting of several states is called a cycle attractor (similar to a limit cycle). RBNs are dissipative systems, since each state has only one successor, while having the possibility of having several predecessor states (many states lead to one state), or no predecessor (a state can be reached only from initial conditions, a so called a “Garden of Eden” state). Figure 2 illustrates the state transitions of RBNs. Note that the topological network (with N nodes, each with a Boolean variable, i.e. one bit) is different from the state transition network (with 2 N nodes, each with N bits). One of the main avenues in RBN research is involved with studying how the topological network (structure) determines the properties of the state transition network (function). Figure 2: Example of state transitions. B is a successor state of A and a predecessor of C . States can have many predecessors (e.g. B ), but only one successor. G is a Garden of Eden state since it has no predecessors. The attractor C → D → E → F → C has a period four. [19] 4 A B C D F E H G ... ...