Abstract
Understanding and emulating human creativity is a key factor when developing computer based algorithms devoted to art. This paper presents a new evolutionary approach to art and creativity aimed at comprehending human principles and motivations, behaviors and procedures from an evolutionary point of view. The results, and the collective artwork described, is the product of a new methodology derived from the Interactive Evolutionary Algorithm (IEA), that allowed a team of artists to collaborate following evolutionary procedures in a number of generations while providing interesting information from the creative process developed. Instead of relegating artists to merely evaluating the output of a standard IEA, we provided them with the fundamentals, operators and ideas extracted from IEAs, and asked them to apply those principles while creating a collective artwork. Artists thus focused on their inner creative process with an evolutionary perspective, providing insights that hopefully will allow us to improve future versions of EAs when devoted to art. This paper describes the methodology behind the work and the experiment performed, and analyzes the collective work generated, that eventually became GECCO 2013 Art Design and Creativity Competition award-winning artwork in Amsterdam.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
IEEE Task Force on Creative Intelligence: http://cilab.cs.ccu.edu.tw/ci-tf/.
L. Navarro, C. Cruz, L. Espada, T. Gallego and P. Hernández, coordinated by F. Fernández.
References
J.S. Ackerman, A theory of style. J. Aesthet. Art Crit. 227–237 (1962)
P.J. Angeline, Adaptive and self-adaptive evolutionary computations, in Computational Intelligence: A Dynamic Systems Perspective. IEEE Press (1995), pp. 152–163
M.A. Boden, Computer models of creativity. AI Mag. 30(3), 23 (2009)
R. Burke, S. Gustafson, G. Kendall, A survey and analysis of diversity measures in genetic programming. GECCO 2, 716–723 (2002)
L. Candy, E.A. Edmonds, Explorations in Art and Technology (Springer, Berlin, 2002)
J. Clune, H. Lispon, Endless forms, http://endlessforms.com/. Last access in 2012
G.M. Codignola, Generative recognizable codes from Gaudi, in Generative Art International Conference, Milan (2000)
H. Cohen, How to draw three people in a botanical garden. AAAI 89, 846–855 (1988)
H. Cohen, The further exploits of aaron, painter. Stanf. Hum. Rev. 4(2), 141–158 (1995)
S. Colton, The painting fool (2014), http://www.thepaintingfool.com/about/index.html
C. Fernandes, Abstracting the abstract, http://eadcc.geccocompetitions.com/results/2012/AbstractingTheAbstract/. Last access in 2012
M. Frade, F.F. De Vega, C. Cotta, Modelling video games landscapes by means of genetic terrain programming—a new approach for improving users experience, in Applications of Evolutionary Computing (Springer, Berlin, 2008), pp. 485–490
P. Galanter, What is generative art? Complexity theory as a context for art theory, in GA2003—6th Generative Art Conference. Citeseer (2003)
F. Graa, P. Machado, Evolving assemblages, http://eadcc.geccocompetitions.com/results/2010/EvolvingAssemblages/
G. Greenfield, P. Machado, Simulating artist and critic dynamics, in Proceedings of the International Joint Conference on Computational Intelligence, Funchal, Madeira, Portugal, October 2009, pp. 5–7
T. Kowaliw, J. McCormack, A. Dorin, An interactive electronic art system based on artificial ecosystemics, in 2011 IEEE Symposium on Artificial Life (ALIFE). IEEE (2011), pp. 162–169
W. Langdon, Pfeiffer—a distributed open-ended evolutionary system. AISB 5, 7–13 (2005)
W. Latham, Form synth: the rule-based evolution of complex forms from geometric primitives, in Computers in art, design and animation (Springer, New York, 1989), pp. 80–108
J. MacCormack, M. d’Inverno (eds.), Computers and Creativity (Springer, New York, 2012)
B. MacGregor, Cybernetic serendipity revisited, in Proceedings of the 4th Conference on Creativity and Cognition. ACM (2002), pp. 11–13
J. McCormack, Open problems in evolutionary music and art, in EvoWorkshops (2005), pp. 428–436
M. Mumford, Preface, in F.E.A. Fernandez (ed.), XY (Oxford University Press, Oxford, 2013)
D. Norton, Learning about creativity from an artificial artist, in Proceedings of the Seventh ACM Conference on Creativity and Cognition. ACM (2009), pp. 339–340
A. Pease, S. Colton. 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 (2011)
J. Romero, P. Machado (eds.), The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music. Natural Computing Series (Springer, Berlin, 2007). doi:10.1007/978-3-540-72877-1
I.B. Salins, H. Luga, Artistic image surface generation, http://eadcc.geccocompetitions.com/results/2011/SurfaceEvolution/. Last access in 2012
R. Saunders, J.S. Gero, Artificial Creativity: A Synthetic Approach to the Study of Creative Behaviour. Computational and Cognitive Models of Creative Design V (Key Centre of Design Computing and Cognition, University of Sydney, Sydney, 2001)
J. Secretan, N. Beato, D.B. D’Ambrosio, A. Rodriguez, A. Campbell, J.T. Folsom-Kovarik, K.O. Stanley, Picbreeder: a case study in collaborative evolutionary exploration of design space. Evol. Comput. 19(3), 373–403 (2011)
H. Takagi, Interactive evolutionary computation, in Proccedings of the 5th International Conference on Soft Computing (1998), pp. 41–50
M. Tomassini, L. Vanneschi, F. Fernández de Vega, G. Galeano, A study of diversity in multipopulation genetic programming, in Artificial Evolution (Springer Berlin Heidelberg, 2004), pp. 243–255
M.G. Valdez, L. Trujillo, F.F. de Vega, J.J. Merelo, G. Olague, Evospace-interactive: a framework to develop distributed collaborative–interactive evolutionary algorithms for artistic design, in Proceedings EvoMusart 2013 (2013)
F. Fernandez de Vega, L. Navarro, C. Cruz, F. Chavez, L. Espada, P. Hernndez, T. Gallego. Unplugging evolutionary algorithms: on the sources of novelty and creativity, in 2013 IEEE Congress on Evolutionary Computation (CEC). IEEE (2013), pp. 2856–2863
Acknowledgments
This work was partially supported by projects TIN2011-28627-C04-03 (ANYSELF), awarded by the Spanish Ministry of Science and Innovation, GRU10029 Regional Government of Extremadura, Consejería de Economía, Comercio e Innovación and FEDER.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Fernández de Vega, F., Cruz, C., Navarro, L. et al. Unplugging Evolutionary Algorithms: an experiment on human-algorithmic creativity. Genet Program Evolvable Mach 15, 379–402 (2014). https://doi.org/10.1007/s10710-014-9225-1
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10710-014-9225-1