The evolution of emergent computation in cellular automata

How does an evolutionary process interact with a decentralized, distributed system in order to produce globally coordinated behavior? Using a genetic algorithm (GA) to evolve cellular automata (CAs), it is shown that emergent coordination occurs when evolution takes advantage of the underlying medium's potential to form embedded particles. The particles, typically walls or defects between homogeneous domains, are designed by the evolutionary process to resolve global conflicts in the system. Descriptions of typical solutions discovered by the GA, and the discovered coordination algorithm in terms of embedded particles dynamics are presented. The particle-level description is also employed to analyze the evolutionary pathway through which the solutions were discovered. The results have implications both for understanding emergent collective behavior in natural systems and for the automatic programming of decentralized spatially extended multiprocessor systems.