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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- 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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Related methods
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