Binding representational spaces of colors and emotions for creativity

Abstract To implement cognitive functions such as creativity, or the ability to create analogies and metaphors, it is important to have mechanisms binding different representational spaces. The paper discusses this issue in the broader context of having a “artist” robot, able to process his visual perception, to use his experience and skills as a painter, and to develop a creative digital artefact. In this context, two different spaces of color representation are respectively used to associate a linguistic label and an emotional value to color palettes. If the goal is to build an image that communicates a desired emotion, the robot can use a neural architecture to choose the most suitable palette. The experience concerning palette-emotion association is derived from the analysis of data enriched with textual description available on the web. The representation of colors and palettes is obtained by using neural networks and self association mechanisms with the aim of supporting the choice of the palette.