Towards the Development of Artificial Art Critics

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Reference

Juan Romero, Penousal Machado, Maria Luisa Santos Ares: Towards the Development of Artificial Art Critics. In: Generative Art 2003.

DOI

Abstract

This paper proposes a framework for the simplification of the development of Artificial Art Critics. We provide two basic elements: an architecture that consists of two main modules for the pre-processing and classification of an artwork, and a validation methodology that consists of several stages, such as the objective evaluation of an artwork (with targets like author or style identification) and a dynamic evaluation that implies the integration of the Artificial Art Critic into a multi-agent environment. We also present some experimental results concerning the first stage of the validation methodology. The results show the ability of the system to identify the author of a musical piece and its adaptive capacity to determine the relevant features of the musical piece.

Extended Abstract

Bibtex

Used References

[1] A. Pazos, A. Santos, B. Arcay, J. Dorado, J: Romero, and J. Rodríguez. An Application Framework for Building Evolutionary Computer Systems in Music. Leonardo, 36(1), 2003

[2] S. Baluja, D. Pomerleau, and T. Jochem. Towards Automated Artificial Evolution for Computer-Generated Images. In Connection Science 6, No. 2, pp. 325–354. 1994.

[3] David Cope. Experiments in Musical Intelligence. Madison, WI: A-R Editions, 1996.

[4] Rudolf Arnheim. Entropy and Art. University of California Press, 1971.

[5] P. Machado and A. Cardoso. All the truth about NEvAr. Applied Intelligence, Special issue on Creative Systems, Bentley, P. Corne, D. (eds), Vol. 16, Nr. 2, pp. 101–119, Kluwer Academic Publishers, 2002.

[6] L. Spector and A. Alpern, Criticism, Culture and the Automatic Generation of Artworks. In Proceedings Twelfth National Conference on Artificial Intelligence (AAAI-94), August 1-4, pp. 3–8. AAAI Press. 1994.

[7] B. Manaris, D. Vaughan, C. Wagner, J. Romero and R. Davis. Evolutionary Music and the Zipf-Mandelbrot Law: Developing Fitness Functions for Pleasant Music. In Lecture Notes in Computer Science, Applications of Evolutionary Computing – EvoWorkshops 2003, LNCS 2611, pp. 522-534, Springer-Verlag, 2003


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http://www.generativeart.com/on/cic/papersGA2003/a15.htm

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