Combinatorial Meta Search

Machine learning approaches to computational creativity learn a generative model from a set of exemplars. We introduce combinatorial meta search, an approach for manipulating and combining different learned generative models. We hypothesize that combinatorial meta search can discover new generative models for which data may never have existed and thus expand the space of possible creative artifacts that can be generated.