2 Evolutionary Algorithms Accidents will occur in the best regulated families. —Charles Dickens, David Copperfield Evolutionary algorithms, as the adjective implies, take their inspiration from the macro principles of biology rather than its micro principles, as artificial neural nets do. Indeed, in both form and function, they mirror the dynamics of a theory whose discovery by Charles Darwin in the mid 1800s constitutes one of man’s greatest contributions to science. Evolution as Metaphor When Darwin’s The Origin of the Species was published in 1859, bio- logical ignorance was widespread in the world. Most people believed life on earth had originated by heavenly decree; little or nothing was known of the principles of heredity, fertilization, or the development of the mature animal from an embryo. Darwin’s theory of natural selection— a radical departure from currently accepted beliefs—was so sweeping in scope that it was able to account for all these phenomena, in addition to the wide variation in the earth’s species and the complex inter- relationships among all living creatures. It completely revolutionized nineteenth century natural science revealing a logical and evincible mechanism, called natural selection or survival of the fittest, by which all plants and animals had slowly evolved from earlier forms. The empir- ical evidence supporting Darwin’s theory, as manifest in the fossil record, was so compelling, as to make his ideas almost irrefutable. What Isaac Newton had done for the physical sciences two centuries earlier, Darwin did for biology.