2023/01/30 by Alexey Kazarnikov, Nadja Ray, Kazarnikov, Alexey +7 · 1 citation
Computer Science · #Cellular Automata and Applications #Cellular Automata and Lattice Gases (nlin.CG) #FOS: Computer and information sciences #FOS: Physical sciences #Methodology (stat.ME)
paper · pdf · doi:10.48550/arxiv.2301.13320
openalex publication_date 2023/01/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.