Cellular automata are like “Life”, only better! Find out how scientists use these models to study the dynamics of ecosystems, of fluid flows, gas dynamics, sand piles, magnetic materials, waves . . . . “Automata” means the possible conditions are represented by a discrete set of states, with rules for transitions from state to state. Spatial structure is incorporated by dividing the domain up into discrete “cells” and by making the transition rules depend on not only the state of the cell itself but also of its neighbors. These models can give a lot of understanding into the role of spatial structure (even in very complex domains) and interactions on the overall dynamics, while remaining computationally simple.
from: Glenn Flierl
Cellular Automata (CA) are a scheme for computing using local rules and local communication. Typcally a CA is defined on a grid, with each point on the grid representing a cell with a finite number of states. A transition rule is applied to each cell simultaneously. Typical transition rules depend on the state of the cell and its (4 or 8) nearest neighbors, although other neighborhoods are used. CAs have applications in parallel computing research, physical simulations, and biological simulations.