  We propose a flexible, co-creative framework bringing together multiple
machine learning techniques to assist human users to efficiently produce
effective creative designs. We demonstrate its potential with a perfume bottle
design case study, including human evaluation and quantitative and qualitative
analyses.

Human-Computer Interaction;Artificial Intelligence;Machine Learning