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Natural Computing

Adapt and Survive

Using evolution to design real things -- nuclear reactors and financial trading systems -- may not be a surprise to every Dr. Dobb's reader. Genetic algorithms in their modern form have been around since the 1970s. Their sweet spot has always been design in a large search space with a well-defined and easily measured fitness function.

By contrast, the idea of incorporating evolution and adaptability into the operational fabric of engineering systems is a whole new departure. Instead of leading to the construction of a high-precision machine that can handle every possibility, such designs adapt to possibilities the designers cannot anticipate -- what Jet Propulsion Laboratory's Glenn Reeves calls "unknown unknowns." If devices can combine evolutionary software with flexible engineering substrates (like programmable logic arrays) to circumvent errors, they become self-healing and adaptive organisms. If design principles combine evolutionary adapability with a hierarchical feedback-control framework to ensure safety to life, property, and the environment, the resulting systems can be safer, cheaper, and far longer-lived.

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