Incorporating Characteristics of Human Creativity into an Evolutionary Art Algorithm

Resource type
Date created
2009
Authors/Contributors
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.
Document
Published as
DiPaola, S. & Gabora, L. (2009). Incorporating characteristics of human creativity into an evolutionary art algorithm. Genetic Programming and Evolvable Machines, 10 (2), 97-110. DOI 10.1007/s10710-008-9074-X
Publication title
Genetic Programming and Evolvable Machines
Document title
Incorporating characteristics of human creativity into an evolutionary art algorithm
Date
2009
Volume
10
Issue
2
First page
97
Last page
110
Publisher DOI
10.1007/s10710-008-9074-X
Copyright statement
Copyright is held by the author(s).
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You are free to copy, distribute and transmit this work under the following conditions: You must give attribution to the work (but not in any way that suggests that the author endorses you or your use of the work); You may not use this work for commercial purposes; You may not alter, transform, or build upon this work.
Scholarly level
Peer reviewed?
Yes
Language
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