Cellular Automata

Cellular Automata (CAs) are decentralized spatially extended systems consisting of large numbers of simple and identical components with local connectivity. Such systems have the potential to perform complex computations with a high degree of efficiency and robustness, as well as to model the behavior of complex systems from nature. CAs have been studied extensively in the natural sciences, mathematics and in computer science. They have been considered as mathematical objects about which formal properties can be proved and have been used as parallel computing devices, both for high-speed simulation of scientific models as for computational tasks such as image processing. CAs have also been used as abstract models for studying ‘emergent’ cooperative or collective behavior in complex systems [e.g. Sloot 2001a [46]]. In addition CAs have been successfully applied to the simulation of a large variety of dynamical systems such as biological processes including pattern formation, earthquakes, urban growth, galaxy formation and most notably in studying fluid dynamics. Their implicit spatial locality allows for very efficient high performance implementations and incorporation into advanced programming environments.