Threading Cellular Architecture Geometries

Abstract

AbstractIn the massive computer architecture known as cellular automata (CA), finite-state machines, also known as finite-state automata, are arranged in a discontinuous network that permits local interactions between neighbors. As self-organizing artificial systems, such as neural networks and genetic algorithms, developed from vast systems formed with essential elements and just local interactions, CA is mainly related to artificial intelligence (AI) (a seed interacts with its own neighbors, which are usually just the cells closer to the seed as an activator). In order to produce architectural spaces of various sizes, this research develops digital experiments that analyze the interactions between environmental conditions as input, CA as generator/propagator, and geometrical emergent patterns from knitting and weaving processes as translators/mediators. This method functions as a bottom-up strategy in which information from the environment can influence the activation and deactivation of rules, theoretically fostering a reprogrammable structure that can evolve.