Abstract
The Painting Fool is software that we hope will one day be taken seriously as a creative artist in its own right. This aim is being pursued as an Artificial Intelligence (AI) project, with the hope that the technical difficulties overcome along the way will lead to new and improved generic AI techniques. It is also being pursued as a sociological project, where the effect of software which might be deemed as creative is tested in the art world and the wider public. In this chapter, we summarise our progress so far in The Painting Fool project. To do this, we first compare and contrast The Painting Fool with software of a similar nature arising from AI and graphics projects. We follow this with a discussion of the guiding principles from Computational Creativity research that we adhere to in building the software. We then describe five projects with The Painting Fool where our aim has been to produce increasingly interesting and culturally valuable pieces of art. We end by discussing the issues raised in building an automated painter, and describe further work and future prospects for the project. By studying both the technical difficulties and sociological issues involved in engineering software for creative purposes, we hope to help usher in a new era where computers routinely act as our creative collaborators, as well as independent and creative artists, musicians, writers, designers, engineers and scientists, and contribute in meaningful and interesting ways to human culture.
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- 1.
The web pages for which are here: ccg.doc.ic.ac.uk.
- 2.
Available at www.contextfreeart.org.
References
Abdennadher, S., & Frühwirth, T. (2003). Essentials of constraint programming. Berlin: Springer.
Anon (1934). Are thinking machines possible? Meccano Magazine, June.
Baars, B. (1988). A cognitive theory of consciousness. Cambridge: Cambridge University Press.
Boden, M. (2003). The creative mind: myths and mechanisms (2nd ed.). London: Routledge.
Boden, M. (2010). Creativity and art. Three roads to success. London: Oxford University Press.
Carlsson, M., Ottosson, G., & Carlson, B. (1997). An open-ended finite domain constraint solver. In Proceedings of programming languages: implementations, logics, and programs.
Charnley, J. (2010). A global workspace framework for combined reasoning. PhD thesis, Department of Computing, Imperial College, London, UK.
Cohen, H. (1995). The further exploits of AARON, painter. Stanford Humanities Review, 4(2).
Collomosse, J., & Hall, P. (2006). Salience-adaptive painterly rendering using genetic search. International Journal on Artificial Intelligence Tools (IJAIT), 15(4), 551–576.
Colton, S. (2002). Automated theory formation in pure mathematics. Berlin: Springer.
Colton, S. (2008a). Automatic invention of fitness functions, with application to scene generation. In Proceedings of the EvoMusArt workshop.
Colton, S. (2008b). Creativity versus the perception of creativity in computational systems. In Proceedings of the AAAI spring symposium on creative systems.
Colton, S. (2008c). Experiments in constraint-based automated scene generation. In Proceedings of the 5th international joint workshop on computational creativity.
Colton, S. (2010). Stroke matching for paint dances. In Proceedings of computational aesthetics.
Colton, S., & Browne, C. (2009). Evolving simple art-based games. In Proceedings of the EvoGames workshop.
Colton, S., Cook, M., & Raad, A. (2011). Ludic considerations of tablet-based evo-art. In Proceedings of the EvoMusArt workshop.
Colton, S., Valstar, M., & Pantic, M. (2008). Emotionally aware automated portrait painting. In Proceedings of the 3rd international conference on digital interactive media in entertainment and arts.
Cook, M., & Colton, S. (2011). Automated collage generation—with more intent. In Proceedings of the international conference on computational creativity.
El-Hage, J. (2009). Linguistic analysis for the painting fool. Master’s thesis, The Computer Laboratory, University of Cambridge, UK.
Faure-Walker, J. (2006). Painting the digital river. New York: Prentice Hall.
Galanter, P. (2010). The problem with evolutionary art is …. In Proceedings of the EvoMusArt workshop.
Hull, M., & Colton, S. (2007). Towards a general framework for program generation in creative domains. In Proceedings of the 4th international joint workshop on computational creativity.
Krzeczkowska, A. (2009). Automated collage generation from text. Master’s thesis, Department of Computing, Imperial College, London, UK.
Krzeczkowska, A., El-Hage, J., Colton, S., & Clark, S. (2010). Automated collage generation—with intent. In Proceedings of the 1st international conference on computational creativity.
Machado, P., & Cardoso, A. (2002). All the truth about NEvAr. Applied Intelligence, 16(2), 101–118.
McCorduck, P. (1991). AARON’s code: meta-art, artificial intelligence, and the work of Harold Cohen. New York: Freeman.
McCormack, J. (2008). Evolutionary L-systems. In P. Hingston, L. Barone & Z. Michalewicz (Eds.), Design by evolution: advances in evolutionary design (pp. 168–196). Berlin: Springer.
Mihalcea, R., & Tarau, P. (2004). TextRank: bringing order into texts. In Proceedings of the conference on empirical methods in natural language processing.
Pease, A., & Colton, S. (2011). On impact and evaluation in computational creativity: a discussion of the Turing test and an alternative proposal. In Proceedings of the AISB symposium on AI and philosophy.
Perez y Perez, R. (2007). Employing emotions to drive plot generation in a computer-based storyteller. Cognitive Systems Research, 8(2), 89–109.
Picard, R. (2002). Affective computing. Cambridge: MIT Press.
Ritchie, G. (2007). Some empirical criteria for attributing creativity to a computer program. Minds and Machines, 17, 67–99.
Romero, J., & Machado, P. (Eds.) (2007). The art of evolution: a handbook on evolutionary art and music. Berlin: Springer.
Sims, K. (1994). Evolving virtual creatures. In Proceedings of SIGGRAPH (pp. 15–22).
Strothotte, T., & Schlechtweg, S. (2002). Non-photorealistic computer graphics. San Mateo: Morgan Kaufmann.
Todd, S., & Latham, W. (1992). Evolutionary art and computers. San Diego: Academic Press.
Torres, P., Colton, S., & Rüger, S. (2008). Experiments in example-based image filter retrieval. In Proceedings of the cross-media workshop.
Valstar, M., & Pantic, M. (2006). Biologically vs. logic inspired encoding of facial actions and emotions in video. In Proceedings of the IEEE international conference on multimedia and expo.
Acknowledgements
We would like to thank the organisers and participants of the 2009 Dagstuhl seminar on Computational Creativity for their very interesting discussions, debates and performances, and for permission to use their images in the paint dances. We would also like to thank the Dagstuhl staff for their efforts in making the event very enjoyable. The anonymous reviewers for this chapter provided some excellent food for thought with relation to the arguments that we put forward. These comments have greatly enhanced our understanding of the issues, and have led to a much improved chapter. Many members of the Computational Creativity community have expressed support and provided much input to The Painting Fool project, for which we are most grateful. We owe a great deal of gratitude to the many collaborators who have contributed time and expertise on The Painting Fool and related projects. These include Anna Krzeczkowska, Jenni Munroe, Charlotte Philippe, Azalea Raad, Maja Pantic, Fai Greeve, Michel Valstar, John Charnley, Michael Cook, Shafeen Tejani, Pedro Torres, Stephen Clark, and Stefan Rüger.
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Colton, S. (2012). The Painting Fool: Stories from Building an Automated Painter. In: McCormack, J., d’Inverno, M. (eds) Computers and Creativity. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31727-9_1
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