Generating Code For Expressing Simple Preferences: Moving On From Hardcoding And Randomness
Michael Lee Cook, Simon Colton · ICCC · 2015
Software expressing intent and justifying creative decisions are important considerations when building systems in the context of Computational Creativity. However, getting software to express subjective opinions like simple preferences is difficult without mimicking existing people’s opinions or using random choice. In this paper, we propose an alternative way of enabling software to make meaningful decisions in smallscale subjective scenarios, such as choosing a favourite colour. Our system uses a combination of metrics as a fitness function for evolving short pieces of code that choose between artefacts. These ‘preference functions’ can make choices between simple items that are neither random nor based on an already existing opinion, and additionally have a sense of consistency. We describe the system, offer some example results from the work and suggest how this might lead to further developments in generative subjectivity in the future.