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  2. 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.

  3. Rule 30 - Wikipedia

    en.wikipedia.org/wiki/Rule_30

    If the left, center, and right cells are denoted (p,q,r) then the corresponding formula for the next state of the center cell can be expressed as p xor (q or r). It is called Rule 30 because in binary, 00011110 2 = 30. The following diagram shows the pattern created, with cells colored based on the previous state of their neighborhood.

  4. Von Neumann cellular automaton - Wikipedia

    en.wikipedia.org/wiki/Von_Neumann_cellular_automaton

    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 ...

  5. Second-order cellular automaton - Wikipedia

    en.wikipedia.org/.../Second-order_cellular_automaton

    In each time step t, for each cell c of the automaton, this function is applied to the neighborhood of c to give a permutation σ c. Then, this permutation σ c is applied to the state of cell c at time t − 1, and the result is the state of the cell at time t + 1. In this way, the configuration of the automaton at each time step is computed ...

  6. Elementary cellular automaton - Wikipedia

    en.wikipedia.org/wiki/Elementary_cellular_automaton

    In mathematics and computability theory, an elementary cellular automaton is a one-dimensional cellular automaton where there are two possible states (labeled 0 and 1) and the rule to determine the state of a cell in the next generation depends only on the current state of the cell and its two immediate neighbors.

  7. 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.

  8. 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.

  9. Rule 110 - Wikipedia

    en.wikipedia.org/wiki/Rule_110

    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 .