Cellular Automaton

Cellular automata (CA) are computational models where simple, locally interacting elements create complex, emergent patterns. Current research focuses on developing efficient CA libraries, exploring the relationship between rule complexity and emergent intelligence, and applying machine learning techniques like convolutional neural networks and transformers to classify and generate CA behaviors, including for applications like image restoration and wildfire prediction. This field is significant for its ability to model complex systems across diverse disciplines, from neuroscience to materials science, and its potential to advance our understanding of emergence and self-organization.