The synchronous approach assumes the presence of a global clock to ensure all cells are updated together. Nehaniv in 1998) allows one to emulate exactly the behaviour of a synchronous cellular automaton via an asynchronous one constructed as a simple modification of the synchronous cellular automaton (Nehaniv 2002).While convenient for preparing computer systems, this might be an unrealistic assumption if the model is intended to represent, for example, a living system where there is no evidence of the presence of such a device. Correctness of this method however has only more recently been rigorously proved (Nehaniv, 2004).There is always a question of how simple these models should be in order to adequately describe what is being modelled.The use of asynchronous models can allow an extra level of realism in the model.In contrast, an asynchronous cellular automaton is able to update individual cells independently, in such a way that the new state of a cell affects the calculation of states in neighbouring cells.
Cellular automata are defined by a grid, a finite set of elementary states, a neighborhood and a local function which defines the dynamics.
Often, models like cellular automata are used to help understanding of processes that work in real life.
By building simplified models, new insights can be learned.
We compare synchronous to asynchronous and sequential updatings.
Focusing on two automata, we discuss how update changes destroy typical structures of these rules.