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Stochastic Cellular Automata

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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Stochastic Cellular Automata — Probabilistic Grid-Based Simulation of Complex Spatial Systems

Registro del método taxonómico · process-pipeline / simulation

Wolfram, S. (2002). A New Kind of Science. Wolfram Media, Champaign, IL. · ISBN 9781579550080
Chopard, B., Droz, M. (1998). Cellular Automata Modeling of Physical Systems. Cambridge University Press, Cambridge. · ISBN 9780521679459

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Métodos relacionados

Generado a partir del grafo de métodos y mostrado como relaciones sugeridas por la máquina; no se infiere ninguna afirmación de evidencia.

Same method familyAgent-Based Modelingmachine-suggested · Relational suggestion, not evidence.Same method familyCellular Automatamachine-suggested · Relational suggestion, not evidence.Same method familyDiscrete-Event Simulationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMarkov Modelmachine-suggested · Relational suggestion, not evidence.See alsoMONTE-CARLO-SIMULATIONmachine-suggested · Relational suggestion, not evidence.