# Parameter estimation for cellular automata

arXiv: https://arxiv.org/abs/2301.13320 · HTML: https://mlsanity.com/paper/2301.13320/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jan 2023.

## Built on by (most cited first, 1 of 1)

- [Cellular Automaton With CNN](https://mlsanity.com/paper/2503.02652/) (2025)

## Abstract (arXiv)

Self-organizing complex systems can be modeled using cellular automaton models. However, the parametrization of these models is crucial and significantly determines the resulting structural pattern. In this research, we introduce and successfully apply a sound statistical method to estimate these parameters. The decisive difference to earlier applications of such approaches is that, in our case, both the CA rules and the resulting patterns are discrete. The method is based on constructing Gaussian likelihoods using characteristics of the structures, such as the mean particle size. We show that our approach is robust for the method parameters, domain size of patterns, or CA iterations.