Finally, it presents the different fields in which CA have been applied.The extensive bibliography provided with the article will be of help to the new entrant as well as researchers working in this field. A cellular automaton is a decentralized computing model providing an excellent platform for performing complex computation with the help of only local information.
Researchers, scientists and practitioners from different fields have exploited the CA paradigm of local information, decentralized control and universal computation for modeling different applications.
This article provides a survey of available literature of some of the methodologies employed by researchers to utilize cellular automata for modeling purposes.
1 Citation Context ..widely varies from one automata to another (e.g., [2,3]).
Only few theoretical studies exist on the influence of asynchronism.
We characterize formally the sensitivity to asynchronism of the relaxation times for 52 of the 64 considered automata.
Our work relies on the design of probabilistic tools that enable to predict the global behaviour by counting local configuration patterns.This is achieved by introduction of a synchronization substratum which locally keeps track of the passage of time in a local neighborhood in a manner that keeps all cells locally in-step.The generality of this mechanism is guaranteed by a general mathematical theorem (due to the author) that allows any synchronous cellular automata configuration and rule to be realized asynchronously in such a way the the behavior of the original synchronous cellular automata can be recovered from that of the corresponding asynchronous cellular automaton. This paper presents a theoretical study of the selection pressure in asynchronous cellular evolutionary algorithms (c EAs).These tools may be of independent interest since they provide a convenient framework to deal exhaustively with the tedious case analysis inherent to this kind of study.The remaining 12 automata (only 5 after symmetries) appear to exhibit interesting complex phenomena (such as polynomial/exponential/infinite phase transitions).We show that, to a good approximation, randomly structured and panmictic populations have the same growth behavior ..." We present discrete stochastic mathematical models for the growth curves of synchronous and asynchronous evolutionary algorithms with populations structured according to a random graph.