Skip to main content
Article thumbnail
Location of Repository

Incorporating characteristics of human creativity into an evolutionary art algorithm (journal article)

By Dr. Steven DiPaola and Dr. Liane M. Gabora

Abstract

A perceived limitation of evolutionary art and design algorithms is that they rely on human intervention; the artist selects the most aesthetically pleasing variants of one generation to produce the next. This paper discusses how computer generated art and design can become more creatively human-like with respect to both process and outcome. As an example of a step in this direction, we present an algorithm that overcomes the above limitation by employing an automatic fitness function. The goal is to evolve abstract portraits of Darwin, using our 2nd generation fitness function which rewards genomes that not just produce a likeness of Darwin but exhibit certain strategies characteristic of human artists. We note that in human creativity, change is less choosing amongst randomly generated variants and more capitalizing on the associative structure of a conceptual network to hone in on a vision. We discuss how to achieve this fluidity algorithmically

Topics: Cognitive Psychology, Artificial Intelligence
Year: 2009
OAI identifier: oai:cogprints.org:6767
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://cogprints.org/6767/1/di... (external link)
  • http://cogprints.org/6767/ (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.