Learnable evolution model: Difference between revisions

Revision as of 12:58, 22 March 2007

Revision as of 21:42, 29 September 2007

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{{Original research|date=September 2007}}

{{OR}}

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 solution|candidate problem solution]]s). Unlike standard, Darwinian-type evolutionary computation methods that use random or semi-random operators for generating new individuals (such as [[mutation (genetic algorithm)|mutation]]s and/or [[genetic recombination|recombination]]s), LEM employs hypothesis generation and instantiation operators.