Process / pipelineSimulation / optimization

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

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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Sources

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

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Referenced by

ScholarGateStochastic Cellular Automata (Stochastic Cellular Automata — Probabilistic Grid-Based Simulation of Complex Spatial Systems). Retrieved 2026-06-04 from https://scholargate.app/en/simulation/stochastic-cellular-automata