cellular automaton - definizione. Che cos'è cellular automaton
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Cosa (chi) è cellular automaton - definizione

DISCRETE MODEL STUDIED IN COMPUTABILITY THEORY, MATHEMATICS, PHYSICS, COMPLEXITY SCIENCE, THEORETICAL BIOLOGY AND MICROSTRUCTURE MODELING
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  • Rule 110
  • Rule 30
  • Visualization of a lattice gas automaton. The shades of grey of the individual pixels are proportional to the gas particle density (between 0 and 4) at that pixel. The gas is surrounded by a shell of yellow cells that act as reflectors to create a closed space.
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  • Los Alamos]] ID badge
  • An animation of the way the rules of a 1D cellular automaton determine the next generation.
  • A cellular automaton based on hexagonal cells instead of squares (rule 34/2)
  • ''[[Conus textile]]'' exhibits a cellular automaton pattern on its shell.<ref name=coombs/>
  • A [[torus]], a toroidal shape

cellular automaton         
<algorithm, parallel> (CA, plural "- automata") A regular spatial lattice of "cells", each of which can have any one of a finite number of states. The state of all cells in the lattice are updated simultaneously and the state of the entire lattice advances in discrete time steps. The state of each cell in the lattice is updated according to a local rule which may depend on the state of the cell and its neighbors at the previous time step. Each cell in a cellular automaton could be considered to be a finite state machine which takes its neighbours' states as input and outputs its own state. The best known example is J.H. Conway's game of Life. {FAQ (http://alife.santafe.edu/alife/topics/cas/ca-faq/ca-faq.html)}. Usenet newsgroups: news:comp.theory.cell-automata, news:comp.theory.self-org-sys. (1995-03-03)
cellular automata         
Stochastic cellular automaton         
TYPE OF RANDOM PROCESS INDEPENDENT
User:PierreYvesLouis/Stochastic cellular automaton; Stochastic cellular automata; Probabilistic cellular automata; Probabilistic Cellular Automata; Random cellular automata; Probabilistic cellular automaton
Stochastic cellular automata or probabilistic cellular automata (PCA) or random cellular automata or locally interacting Markov chains are an important extension of cellular automaton. Cellular automata are a discrete-time dynamical system of interacting entities, whose state is discrete.

Wikipedia

Cellular automaton

A cellular automaton (pl. cellular automata, abbrev. CA) is a discrete model of computation studied in automata theory. Cellular automata are also called cellular spaces, tessellation automata, homogeneous structures, cellular structures, tessellation structures, and iterative arrays. 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. For each cell, a set of cells called its neighborhood is defined relative to the specified cell. An initial state (time t = 0) is selected by assigning a state for each cell. A new generation is created (advancing t by 1), according to some fixed rule (generally, a mathematical function) that determines the new state of each cell in terms of the current state of the cell and the states of the cells in its neighborhood. Typically, the rule for updating the state of cells is the same for each cell and does not change over time, and is applied to the whole grid simultaneously, though exceptions are known, such as the stochastic cellular automaton and asynchronous cellular automaton.

The concept was originally discovered in the 1940s by Stanislaw Ulam and John von Neumann while they were contemporaries at Los Alamos National Laboratory. While studied by some throughout the 1950s and 1960s, it was not until the 1970s and Conway's Game of Life, a two-dimensional cellular automaton, that interest in the subject expanded beyond academia. In the 1980s, Stephen Wolfram engaged in a systematic study of one-dimensional cellular automata, or what he calls elementary cellular automata; his research assistant Matthew Cook showed that one of these rules is Turing-complete.

The primary classifications of cellular automata, as outlined by Wolfram, are numbered one to four. They are, in order, automata in which patterns generally stabilize into homogeneity, automata in which patterns evolve into mostly stable or oscillating structures, automata in which patterns evolve in a seemingly chaotic fashion, and automata in which patterns become extremely complex and may last for a long time, with stable local structures. This last class is thought to be computationally universal, or capable of simulating a Turing machine. Special types of cellular automata are reversible, where only a single configuration leads directly to a subsequent one, and totalistic, in which the future value of individual cells only depends on the total value of a group of neighboring cells. Cellular automata can simulate a variety of real-world systems, including biological and chemical ones.