The review shows advancements in cellular automata methods and frameworks for future exploration.
The Gdansk School of Cellular Automata has, over the last decade, developed a coherent program that bridges theory with exploratory computation. We review results on (i) identifying cellular automata from partial, noisy observations, (ii) affine continuous cellular automata (ACCAs) and their links to stochastic and deterministic rules, (iii) relaxed density classification using ACCAs, (iv) parity classification bounds and constructive single-rule solutions, and (v) number-conserving and state-conserving cellular automata across uniform, non-uniform, and non-square grids, including split-and-perturb decompositions, graph-based enumerations, reversible subclasses, and traffic-like particle-flow rules. The survey is written in the spirit of Prof. Danuta Makowiec’s emphasis on combining rigorous analysis with computational experimentation, and is intended to serve both as a guide for newcomers and as a reference point for future work.
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Bołt et al. (2026) studied this question.
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