Using a Contextual Focus Model for an Automatic Creativity Algorithm to Generate Art Work

Abstract

We sought to implement and determine whether incorporating cognitive based contextual focus into a genetic programming fitness function would play a crucial role in enabling the computer system to generate art that humans find “creative” (i.e. possessing qualities of novelty and aesthetic value typically ascribed to the output of a creative artistic process). We implemented contextual focus in the evolutionary art algorithm by giving the program the capacity to vary its level of fluidity and functional triggered dynamic control over different phases of the creative process. The domain of portrait painting was chosen because it requires both focused attention (analytical thought) to accomplish the primary goal of creating portrait sitter resemblance as well as defocused attention (associative thought) to creativity deviate from resemblance i.e., to meet the broad and often conflicting criteria of aesthetic art. Since judging creative art is subjective, rather than use quantitative analysis, a representative subset of the automatically produced art-work from this system was selected and submitted to many peer reviewed and commissioned art shows, thereby allowing it to be judged positively or negatively as creative by human art curators, reviewers and the art gallery going public.