Arnheim, R.,Art and Visual Perception: A Psychology of the Creative Eye, University of California Press, 1954.
Arnheim, R.,Entropy and Art, University of California Press, 1971.
Baluja, S., Pomerleau, D. and Jochem, T., “Towards Automated Artificial Evolution for Computer-generated Images,”Connection Science, 6, 2–3, pp. 325–354, 1994.
Burton, A.R. and Vladimirova, T., “Applications of Genetic Techniques to Musical Composition,”Computer Music Journal,23,4, 1999.
Graves, M.,Design Judgement Test, The Psychological Corporation, New York, 1948.
Johnson, C. and Romero, J., “Genetic Algorithms in Visual Art and Music,”Leonardo, 35, 2, pp. 175–184, 2002.
Machado, P. and Cardoso, A., “NEvAr—The Assessment of an Evolutionary Art Tool,” inProceedings of the AISB’00 Symposium on Creative & Cultural Aspects and Applications of AI & Cognitive Science 2000 (Wiggins, G., ed.), Birmingham, UK, 2000.
Machado, P. and Cardoso, A., “Computing Aesthetics,” inProceedings of the XIVth Brazilian Symposium on Artificial Intelligence SBIA’98 (Oliveira F., ed),LNAI Series, Springer-Verlag, pp. 219–229, Porto Alegre, Brazil, 1998.
Machado, P. and Cardoso, A., “All the Truth about NEvAr,”Applied Intelligence, Special issue on Creative Systems, 16, 2, (Bentley, P. and Corne, D., eds.), Kluwer Academic Publishers, pp. 101–119, 2002.
Machado, P., Romero, J., Santos, M.L., Cardoso, A. and Manaris, B., “Adaptive Critics for Evolutionary Artists,”Lecture Notes in Computer Science, Applications of Evolutionary Computing, LNCS 3005, Springer-Verlag, pp. 437–446, 2004.
Manaris, B., Purewal, T. and McCormick, C., “Progress Towards Recognizing and Classifying Beautiful Music with Computers,” inProceedings of EEE SoutheastCon, Columbia, SC, USA, pp. 52–57, 2002.
Papadopoulos, G. and Wiggins, G., “AI Methods for Algorithmic Composition: A Survey, a Critical View and Future Prospects,” inAISB’99 Symposium on Musical Creativity, Edinburgh, UK, pp. 110–117, 1999.
Romero, J., Machado, P., Santos, A. and Cardoso, A., “On the Development of Critics in Evolutionary Computation Systems,”Lecture Notes in Computer Science, Applications of Evolutionary Computing, LNCS 2611, Springer-Verlag, pp. 559–569, 2003.
Romero, J., Santos, A., Dorado, J., Arcay, B. and Rodriguez, J., “Evolutionary Computation System for Musical Composition,”Mathematics and Computers in Modern Science, World Scientific and Engineering Society Press, pp. 97–102, 2000.
Saunders, R. and Gero, J.S., “The Digital Clockwork Muse: A Computational Model Of Aesthetic Evolution,” inAISB’01 Symposium on Artificial Intelligence and Creativity in Arts and Science, York, UK, 2001.
Svangaard, N. and Nordin, P. “Automated Aesthetic Selection of Evolutionary Art by Distance Based Classification of Genomes and Phenomes using the Universal Similarity Metric,”Lecture Notes in Computer Science, Applications of Evolutionary Computing, LNAI Series, Springer-Verlag, pp. 447–456, 2004.
Takagi, H., “Interactive Evolutionary Computation: Fusion of the Capabilities of EC Optimization and Human Evaluation,” inProceedings of the IEEE, 89, 9, pp. 1275–1296, 2001.
Taylor, R.P., Micolich, A.P. and Jonas, D., “Fractal Analysis of Pollock’s Drip Paintings,”Nature, pp. 399–422, 1999.
Todd, P.M. and Werner, G.M., “Frankestenian Methods for Evolutionary Music Composition,”Musical Networks: Parallel distributed perception and performance, (Griffith, N. and Todd, P. M., eds.), MIT Press, Cambridge, MA, 1998.