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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

    The rule defining the cellular automaton must specify the resulting state for each of these possibilities so there are 256 = 2 2 3 possible elementary cellular automata. Stephen Wolfram proposed a scheme, known as the Wolfram code , to assign each rule a number from 0 to 255 which has become standard.

  4. Cellular automaton - Wikipedia

    en.wikipedia.org/wiki/Cellular_automaton

    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.

  5. Wolfram code - Wikipedia

    en.wikipedia.org/wiki/Wolfram_code

    A code of this type suffixed by an R, such as "Rule 37R", indicates a second-order cellular automaton with the same neighborhood structure. While in a strict sense every Wolfram code in the valid range defines a different rule, some of these rules are isomorphic and usually considered equivalent. For example, rule 110 above is isomorphic with ...

  6. Rule 90 - Wikipedia

    en.wikipedia.org/wiki/Rule_90

    Time-space diagram of Rule 90 with random initial conditions. Each row of pixels is a configuration of the automaton; time progresses vertically from top to bottom. In the mathematical study of cellular automata, Rule 90 is an elementary cellular automaton based on the exclusive or function. It consists of a one-dimensional array of cells, each ...

  7. Rule 184 - Wikipedia

    en.wikipedia.org/wiki/Rule_184

    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]

  8. Rule 110 - Wikipedia

    en.wikipedia.org/wiki/Rule_110

    Among the 88 possible unique elementary cellular automata, Rule 110 is the only one for which Turing completeness has been directly proven, although proofs for several similar rules follow as simple corollaries (e.g. Rule 124, which is the horizontal reflection of Rule 110). Rule 110 is arguably the simplest known Turing complete system.

  9. Reversible cellular automaton - Wikipedia

    en.wikipedia.org/wiki/Reversible_cellular_automaton

    A cellular automaton is defined by its cells (often a one- or two-dimensional array), a finite set of values or states that can go into each cell, a neighborhood associating each cell with a finite set of nearby cells, and an update rule according to which the values of all cells are updated, simultaneously, as a function of the values of their neighboring cells.