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Explanation-based learning
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<p>Explanation-based learning (EBL) is a form of <a href="/facts/Machine_learning/e0w0XJTu">machine learning</a> that exploits a very strong, or even perfect, <a href="/facts/Domain_(software_engineering)/NRnAyFlR">domain</a> theory (i.e. a formal theory of an application domain akin to a <a href="/facts/Domain_model/rSxm7s5a">domain model</a> in <a href="/facts/Ontology_engineering/XzBfzVuC">ontology engineering</a>, not to be confused with Scott's <a href="/facts/Domain_theory/G1wRMK2K">domain theory</a>) in order to make generalizations or form concepts from training examples. It is also linked with <a href="/facts/Encoding_(memory)/H08V1MhT">Encoding (memory)</a> to help with <a href="/facts/Learning/lehEKRjC">Learning</a>. </p>