Academia.eduAcademia.edu

Outline

Partially interactive evolutionary artists

2005, New Generation Computing

Abstract

User fatigue is probably the most pressing problem in current Interactive Evolutionary Computation systems. To address it we propose the use of automatic seeding procedure, phenotype filters, and partial automation fitness assignment. We test this approaches in the visual arts domain. To further enhance interactive evolution applications in aesthetic domains, we propose the use of artificial art critics -systems that perform stylistic and aesthetic valuations of art -presenting experimental results.

References (7)

  1. Arnheim R., Art and Visual Perception: A Psychology of the Creative Eye, University of California Press, 1954.
  2. Arnheim R., Entropy and Art, University of California Press, 1971.
  3. Baluja, S., Pomerleau, D. and Jochem, T., "Towards Automated Artificial Evolution for Computer-generated Images", Connection Science, 6, 2-3, pp. 325-354, 1994.
  4. Burton A. R., Vladimirova T., "Applications of Genetic Techniques to Musical Composition", Computer Music Journal, 23, 4, 1999.
  5. Graves, M., Design Judgement Test, The Psychological Corporation, New York, 1948.
  6. Johnson C., Romero J., "Genetic Algorithms in Visual Art and Music", Leonardo, 35, 2, pp. 175-184, 2002.
  7. Machado P., Cardoso A., "NEvAr -The Assessment of an Evolutionary Art Tool", in Proceedings of the AISB'00 Symposium on Creative & Cultural Aspects