Editing Inductive logic programming (section)

=== Evolutionary learning ===
[[Evolutionary algorithm]]s in ILP use a population-based approach to evolve hypotheses, refining them through selection, crossover, and mutation. Methods like [[EvoLearner]] have been shown to outperform traditional approaches on structured machine learning benchmarks. <ref>{{cite conference |last1=Heindorf |first1=Stefan |last2=Blübaum |first2=Lukas |last3=Düsterhus |first3= Nick |last4=Werner |first4=Till |last5=Golani |first5=Varun Nandkumar |last6=Demir |first6=Caglar |last7=Ngonga Ngomo |first7=Axel-Cyrille |title=EvoLearner: Learning Description Logics with Evolutionary Algorithms |conference=WWW |date=2022|arxiv=2111.04879 }}</ref>