Does it make sense to believe that computational approaches to creativity will facilitate the understanding of creativity? Is it worth to investigate computational tools and environments that might help humans being creative? Is it feasible to build programs that we could classify as creative? For those, like us, who don't accept creativity as some kind of divine inspiration, and don't ascribe its origin to an innate intuition talent, i.e., for those who don't adopt what Margaret Boden (1990) called the inspirational and romantic views of creativity, the idea of exploring computational approaches to creativity is far from being a waste of time and resources: creativity is consensually accepted as a fundamental issue of intelligence and one of the most remarkable characteristics of the human mind, and it seems inconceivable for us to assume the research of intelligence (natural or artificial) without considering such an outstanding aspect.
Creativity is hard to measure, observe and interpret. Its study has been a challenge for many scientists and researchers, particularly for those from areas such as Cognitive Science and Psychology. In recent years, the subject attracted a growing number of AI researchers who have been working towards the study and proposal of abstract explanation theories and adequate computational models of creativity. This interest comes from the belief that computational creative systems are potentially effective in a wide range of artistic, technical and scientific domains where innovation is a key issue. Scientific discovery, theorem proving and technical design are just a few examples of application problems suitable for them. Moreover, this endeavour may contribute to the overall understanding of the mechanisms behind creativity.