Parameter Setting in EAs: a 30 Year Perspective
نویسنده
چکیده
Parameterized evolutionary algorithms (EAs) have been a standard part of the Evolutionary Computation community from its inception. The widespread use and applicability of EAs is due in part to the ability to adapt an EA to a particular problem-solving context by tuning its parameters. However, tuning EA parameters can itself be a challenging task since EA parameters interact in highly non-linear ways. In this chapter we provide a historical overview of this issue, discussing both manual (human-in-the-loop) and automated approaches, and suggesting when a particular strategy might be appropriate.
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