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1. The Free On-line Dictionary of Computing (30 December 2018)
evolutionary algorithm

   (EA) An algorithm which incorporates aspects of natural
   selection or survival of the fittest.  An evolutionary
   algorithm maintains a population of structures (usually
   randomly generated initially), that evolves according to rules
   of selection, recombination, mutation and survival, referred
   to as genetic operators.  A shared "environment" determines
   the fitness or performance of each individual in the
   population.  The fittest individuals are more likely to be
   selected for reproduction (retention or duplication), while
   recombination and mutation modify those individuals, yielding
   potentially superior ones.

   EAs are one kind of evolutionary computation and differ from
   genetic algorithms.  A GA generates each individual from
   some encoded form known as a "chromosome" and it is these
   which are combined or mutated to breed new individuals.

   EAs are useful for optimisation when other techniques such as
   gradient descent or direct, analytical discovery are not
   possible.  Combinatoric and real-valued function optimisation
   in which the optimisation surface or fitness landscape is
   "rugged", possessing many locally optimal solutions, are
   well suited for evolutionary algorithms.


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