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| Deterministic Cellular Automata× | Stochastische Zellulare Automaten× | |
|---|---|---|
| Fachgebiet | Simulation | Simulation |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 1940s–1950s | 1940s–1980s |
| Urheber≠ | John von Neumann and Stanislaw Ulam | von Neumann, J. / Ulam, S. (deterministic CA); probabilistic extension formalized by various authors including Wolfram, S. and Chopard, B. |
| Typ≠ | Discrete deterministic grid simulation | Grid-based stochastic simulation |
| Wegweisende Quelle≠ | von Neumann, J. (1966). Theory of Self-Reproducing Automata. University of Illinois Press, Urbana, IL. (Edited and completed by A. W. Burks.) link ↗ | Wolfram, S. (2002). A New Kind of Science. Wolfram Media, Champaign, IL. ISBN: 9781579550080 |
| Aliasnamen | Deterministic CA, Classical Cellular Automata, Rule-based CA, Finite Automata Grid Model | SCA, Probabilistic Cellular Automata, PCA, Stochastic CA |
| Verwandt≠ | 6 | 5 |
| Zusammenfassung≠ | Deterministic Cellular Automata (DCA) is a simulation method that models the evolution of complex systems through a regular grid of cells, each holding a discrete state, updated synchronously at each time step according to a fixed, deterministic rule applied to the cell and its neighbors. The outcome is fully reproducible given the same initial conditions and rule set. | Stochastic Cellular Automata (SCA) extend classical cellular automata by replacing deterministic transition rules with probabilistic ones, allowing each cell on a grid to change state according to a probability distribution conditioned on its neighborhood. This makes SCA a powerful tool for simulating real-world spatial processes where randomness, noise, and uncertainty govern local interactions — from epidemic spread and forest fires to traffic flow and material diffusion. |
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