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Genetic programming
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===Selection=== Selection is a process whereby certain individuals are selected from the current generation that would serve as parents for the next generation. The individuals are selected probabilistically such that the better performing individuals have a higher chance of getting selected.<ref name="field guide" /> The most commonly used selection method in GP is [[tournament selection]], although other methods such as [[fitness proportionate selection]], lexicase selection,<ref>{{Cite book|last=Spector|first=Lee|title=Proceedings of the 14th annual conference companion on Genetic and evolutionary computation |chapter=Assessment of problem modality by differential performance of lexicase selection in genetic programming |url=https://dl.acm.org/citation.cfm?id=2330846|pages=401β408|language=en-US|publisher=ACM|doi=10.1145/2330784.2330846|year=2012|isbn=9781450311786|series=Gecco '12|s2cid=3258264}}</ref> and others have been demonstrated to perform better for many GP problems. Elitism, which involves seeding the next generation with the best individual (or best ''n'' individuals) from the current generation, is a technique sometimes employed to avoid regression.
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