*Genetic algorithms*
(GA) are a computational paradigm
inspired by the mechanics of natural evolution,
including survival of the fittest,
reproduction, and mutation.

Surprisingly, these mechanics can be used to solve (i.e. compute)
a wide range of practical problems, including numeric problems.
*Concrete examples*
illustrate how to encode a problem for solution as a genetic algorithm,
and help explain why genetic algorithms work.

Genetic algorithms are a popular line of current research,
and there are many
*references*
describing both the theory of genetic algorithms
and their use in practical problem solving.