Use of Shape Grammar to Derive Cellular Automata Rule Patterns

Thomas H. Speller

MIT

The purpose of this work is to show how shape grammar can be used to derive cellular automata rules. Searching the potentially infinite space of cellular automata rules for relevance to a particular context has frustrated the wider application of cellular automata as a powerful computing system. An approach is offered using shape grammar to visually depict the desired conditional rules of a behavior or system architecture (a form-function) under investigation, followed by a transcription of these rules as patterns into cellular automata. The combination of shape grammar for managing the input and cellular automata for managing the output brings together the human intuitive approach (visualization of the abstract) with a computational system that can generate large design spaces in a tractable manner.

We believe that the unique approach of utilizing shape grammar as a “visual, graphic code” allows the researcher to understand wide ranges of physical phenomena in such a way as to more easily simulate them through the CA. This graphical input to abstract machine computation for graphical output methodology could provide engineers, physicists, biophysicists, nanoscientists, complexity scientists, and other system architects a more intuitive and quicker means for studying form and function.

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