Comparer des méthodes

	Automates Cellulaires Déterministes	Automates Cellulaires Stochastiques
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1940s–1950s	1940s–1980s
Auteur d'origine	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.
Type	Discrete deterministic grid simulation	Grid-based stochastic simulation
Source fondatrice	von Neumann, J. (1966). Theory of Self-Reproducing Automata. University of Illinois Press, Urbana, IL. (Edited and completed by A. W. Burks.)	Wolfram, S. (2002). A New Kind of Science. Wolfram Media, Champaign, IL. ISBN: 9781579550080
Alias	Deterministic CA, Classical Cellular Automata, Rule-based CA, Finite Automata Grid Model	SCA, Probabilistic Cellular Automata, PCA, Stochastic CA
Apparentées	6	5
Résumé	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.