(Computer science) Genetic Algorithm

Initially the algorithm produces a set of possible solutions. From these the best are chosen and from these another set of solutions based upon the chosen ones are developed, and so on and so forth. We ideally get a better solution each time.

Genetic algorithms are similar to genetics in the real world, where natural selection and survival of the fittest determines what gets passed on to the next generation as the solution evolves.

Genetic algorithms have many applications; one example in a commercial piece of software was a photo enhancement program where you selected the best enhancement, then it generated another set of enhancements based upon that one so you could work towards the best enhancement available. They have also been used in music and synthesis, and most probably have modelling applications too.

last edited (November 2, 2006) by bilderbikkel, Number of views: 3178, Current Rev: 2 (Diff)

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