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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.
Cellular automata are also called cellular spaces, tessellation automata, homogeneous structures, cellular structures, tessellation structures, and iterative arrays. [2] Cellular automata have found application in various areas, including physics , theoretical biology and microstructure modeling.
Pages in category "Cellular automata" The following 29 pages are in this category, out of 29 total. This list may not reflect recent changes. ...
Notable individual patterns, or types of pattern, in cellular automata. Pages in category "Cellular automaton patterns" The following 18 pages are in this category, out of 18 total.
As in Conway's Game of Life, at any point in time each cell may be in one of two states: alive or dead. The Critters rule is a block cellular automaton using the Margolus neighborhood. This means that, at each step, the cells of the automaton are partitioned into 2 × 2 blocks and each block is updated independently of the other blocks.
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.
Technically, they are not cellular automata at all, because the underlying "space" is the continuous Euclidean plane R 2, not the discrete lattice Z 2. They have been studied by Marcus Pivato. [24] Lenia is a family of continuous cellular automata created by Bert Wang-Chak Chan. The space, time and states of the Game of Life are generalized to ...
Rule 30 is an elementary cellular automaton introduced by Stephen Wolfram in 1983. [2] Using Wolfram's classification scheme, Rule 30 is a Class III rule, displaying aperiodic, chaotic behaviour. This rule is of particular interest because it produces complex, seemingly random patterns from simple, well-defined rules.