Evolved Representations and Their Use in Computational Creativity

In any computational process, the representation used plays an important role. Depending on how the representation is chosen, some designs will generally not be representable, restricting the size of the search space. However, the representation can also change the topology of the search space, making some designs more likely to be the outcome of the design process than others. Generally, representations are designed to minimize this bias caused by the representation. This thesis explores how it is possible to develop specific representations that influence a design process in a useful, predictable way, and the possible use of such a method in creative computational processes. The work is based on evolutionary algorithms. These algorithms use an initial representation, which can be referred to as the ‘basic representation’, using symbols from an initial alphabet, the ‘basic genes’. This representation is developed into an ‘evolved representation’ by adding a number of ‘evolved genes‘. These evolved genes encapsulate fixed combinations of basic genes, and protect them from disruption in the evolutionary design process. As a consequence, design processes using the evolved representation will be biased in favour of these gene combinations. If the gene combinations are associated with certain specific features in designs, then a focus is introduced into the design process, centred around designs which show these features. To create appropriate evolved genes with minimal user interaction, a machine learning approach is developed. An evolutionary algorithm creates sample individuals from a set of user provided example designs, and evolved genes are created from successful gene combinations in those sample individuals. The thesis shows that the creation of a focus using an evolved representation can fulfil the procedural definitions of creativity found in the literature, if certain ‘finite system’ restrictions are taken into account. The only additional requirement is the ability to modify the focus in the design process. Since the focus is created by the evolved representation, modifying the evolved representation provides a way to induce these changes in the focus. Creation, use and transformation of evolved representations are demonstrated using two different example applications. In the first example, floor plans of Frank Lloyd Wright’s Prairie Houses are used to create an evolved representation; designs produced using this representation show similarities to the example floor plans. The possibility for a transformation of the search space is demonstrated by a modification of the evolved genes, which changes the proportions of living and service areas in the designs created. In the second example, a tree structure is used for the basic representation, requiring a more complex notion of evolved genes. The evolved representation is created from a set of paintings by the Dutch painter Piet Mondrian and from a window design by Frank Lloyd Wright. Again, designs produced using the representations show similarities to the paintings and the window design respectively. Two different transformations of the focus are demonstrated in this example: mixing the two representations created from the paintings and the window, and adapting the evolved representations for use in a different