Constructive machine learning describes a class of related machine learning problems where the ultimate goal of learning is not to find a good model of the data but instead to find one or more particular instances of the domain which are likely to exhibit desired properties. While traditional approaches choose these domain instances from a given set/databases of unlabeled domain instances, constructive machine learning is typically iterative and searches an infinite or exponentially large instance space.