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  2. Rule 30 - Wikipedia

    en.wikipedia.org/wiki/Rule_30

    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.

  3. Elementary cellular automaton - Wikipedia

    en.wikipedia.org/wiki/Elementary_cellular_automaton

    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. Class 4: Cellular automata which form areas of repetitive or stable states, but also form structures that ...

  4. Wolfram code - Wikipedia

    en.wikipedia.org/wiki/Wolfram_code

    When used on their own without such context, the codes are often assumed to refer to the class of elementary cellular automata, two-state one-dimensional cellular automata with a (contiguous) three-cell neighbourhood, which Wolfram extensively investigates in his book. Notable rules in this class include rule 30, rule 110, and rule 184.

  5. Cellular automaton - Wikipedia

    en.wikipedia.org/wiki/Cellular_automaton

    For next-nearest-neighbor cellular automata, a rule is specified by 2 5 = 32 bits, and the cellular automaton rule space is a 32-dimensional unit hypercube. A distance between two rules can be defined by the number of steps required to move from one vertex, which represents the first rule, and another vertex, representing another rule, along ...

  6. Reversible cellular automaton - Wikipedia

    en.wikipedia.org/wiki/Reversible_cellular_automaton

    This bound is known to be tight for m = 2: there exist n-state reversible cellular automata with two-cell neighborhoods whose time-reversed dynamics forms a cellular automaton with neighborhood size exactly n − 1. [25] For any integer m there are only finitely many two-dimensional reversible m-state cellular automata with the von Neumann ...

  7. Von Neumann cellular automaton - Wikipedia

    en.wikipedia.org/wiki/Von_Neumann_cellular_automaton

    Each FSA of the von Neumann cell space can accept any of the 29 states of the rule-set. The rule-set is grouped into five orthogonal subsets. Each state includes the colour of the cell in the cellular automata program Golly in (red, green, blue). They are a ground state U (48, 48, 48)

  8. Majority problem - Wikipedia

    en.wikipedia.org/wiki/Majority_problem

    Alternatively, a hybrid automaton that runs Rule 184 for a number of steps linear in the size of the array, and then switches to the majority rule (Rule 232), that sets each cell to the majority of itself and its neighbors, solves the majority problem with the standard recognition criterion of either all zeros or all ones in the final state.

  9. Life-like cellular automaton - Wikipedia

    en.wikipedia.org/wiki/Life-like_cellular_automaton

    For instance, in this notation, Conway's Game of Life is denoted 23/3. [2] [3] In the notation used by the Golly open-source cellular automaton package and in the RLE format for storing cellular automaton patterns, a rule is written in the form By/Sx where x and y are the same as in the MCell notation. Thus, in this notation, Conway's Game of ...