Scientific modeling with cellular automata
Joel L. Schiff · Wiley Interdisciplinary Reviews Computational Statistics · 2014
Cellular automata provide a simple environment in which to discretize time and space in order to investigate natural phenomena. In a two‐dimensional scenario for example, the action usually takes place in a rectangular array of cells (although other cell shapes can be used) and each cell exists in one of several ‘states’. In discrete time‐steps all cells change their state in unison according to a locally prescribed rule that takes into account the state of each cell's neighbors at the previous time‐step. This elementary but powerful framework has been highly successful in modeling various scientific phenomena from a broad spectrum of disciplines, some of which are reviewed in this article. Both qualitative and quantitative data can be obtain by the cellular automata approach. This article is categorized under: Algorithms and Computational Methods > Computational Complexity Applications of Computational Statistics > Computational and Molecular Biology Statistical Learning and Exploratory Methods of the Data Sciences > Modeling Methods