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Cellular automata have found application in various areas, including physics, theoretical biology and microstructure modeling. A cellular automaton consists of a regular grid of cells, each in one of a finite number of states, such as on and off (in contrast to a coupled map lattice). The grid can be in any finite number of dimensions.
Golly is a tool for the simulation of cellular automata.It is free open-source software written by Andrew Trevorrow and Tomas Rokicki; [3] it can be scripted using Lua [1] or Python.
Mirek's Cellebration is a freeware one- and two-dimensional cellular automata viewer, explorer, and editor for Windows. It includes powerful facilities for simulating and viewing a wide variety of cellular automaton rules, including the Game of Life, and a scriptable editor. Xlife is a cellular-automaton laboratory by Jon Bennett.
A sample autonomous pattern from Lenia. An animation showing the movement of a glider in Lenia. Lenia is a family of cellular automata created by Bert Wang-Chak Chan. [1] [2] [3] It is intended to be a continuous generalization of Conway's Game of Life, with continuous states, space and time.
Class 1: Cellular automata which rapidly converge to a uniform state. Examples are rules 0, 32, 160 and 232. Class 2: Cellular automata which rapidly converge to a repetitive or stable state. Examples are rules 4, 108, 218 and 250. Class 3: Cellular automata which appear to remain in a random state. Examples are rules 22, 30, 126, 150, 182.
The Rule 110 cellular automaton (often called simply Rule 110) [a] is an elementary cellular automaton with interesting behavior on the boundary between stability and chaos. In this respect, it is similar to Conway's Game of Life .
In von Neumann's cellular automaton, the finite state machines (or cells) are arranged in a two-dimensional Cartesian grid, and interface with the surrounding four cells. As von Neumann's cellular automaton was the first example to use this arrangement, it is known as the von Neumann neighbourhood. The set of FSAs define a cell space of ...
A state of the Rule 184 automaton consists of a one-dimensional array of cells, each containing a binary value (0 or 1). In each step of its evolution, the Rule 184 automaton applies the following rule to each of the cells in the array, simultaneously for all cells, to determine the new state of the cell: [3]