Learnable evolution model: Difference between revisions

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The Learnable Evolution Model (LEM) is a novel, non-Darwinian methodology for [[evolutionary computation]] that employs [[machine learning]] to guide the generation of new individuals (candidate problem solutions). Unlike standard, Darwinian-type evolutionary computation methods that use random or semi-random operators for generating new individuals (such as mutations and/or recombinations), LEM employs hypothesis generation and instantiation operators.