Balancing Act: Variation and Utility in Evolutionary Art
Inhaltsverzeichnis
Referenz
Jon McCormack: Balancing Act: Variation and Utility in Evolutionary Art. In: EvoMUSART 2014, S. 26-37.
DOI
http://link.springer.com/10.1007/978-3-662-44335-4_3
Abstract
Evolutionary Art typically involves a tradeoff between the size and flexibility of genotype space and its mapping to an expressive phenotype space. Ideally we would like a genotypic representation that is terse but expressive, that is, we want to maximise the useful variations the genotype is capable of expressing in phenotype space. Terseness is necessary to minimise the size of the overall search space, and expressiveness can be loosely interpreted as phenotypes that are useful (of high fitness) and diverse (in feature space). In this paper I describe a system that attempts to maximise this ratio between terseness and expressiveness. The system uses a binary string up to any maximum length as the genotype. The genotype string is interpreted as building instructions for a graph, similar to the cellular programming techniques used to evolve artificial neural networks. The graph is then interpreted as a form-building automaton that can construct animated 3-dimensional forms of arbitrary complexity. In the test case the requirement for expressiveness is that the resultant form must have recognisable biomorphic properties and that every possible genotype must fulfil this condition. After much experimentation, a number of constraints in the mapping technique were devised to satisfy this condition. These include a special set of geometric building operators that take into account morphological properties of the generated form. These methods were used in the evolutionary artwork “Codeform”, developed for the Ars Electronica museum. The work generated evolved virtual creatures based on genomes acquired from the QR codes on museum visitor’s entry tickets.
Extended Abstract
Bibtex
Used References
Abelson, H., DiSessa, A.A.: Turtle geometry: the computer as a medium for exploring mathematics. The MIT Press series in artificial intelligence. MIT Press, Cambridge (1982)
Bentley, P.J.: Evolutionary design by computers. Morgan Kaufmann Publishers, San Francisco (1999)
Gruau, F.: Neural Network Synthesis using Cellular Encoding and the Genetic Algorithm. Phd thesis, l’Ecole Normale Superieure de Lyon (1994)
Hornby, G.S.: Generative Representations for Evolutionary Design Automation. PhD thesis, Boston, MA (2003)
Hornby, G.S., Pollack, J.B.: Evolving L-systems to generate virtual creatures. Computers & Graphics 26, 1041–1048 (2001)
Knuth, D.E.: The art of computer programming, world student series edition. World student series, vol. 2. Addison-Wesley, Reading (1972)
Luke, S.: Essentials of Metaheuristics. Lulu Publishing, Department of Computer Science, George Mason University (2009)
McCormack, J.: Aesthetic Evolution of L-Systems Revisited. In: Raidl, G.R., et al. (eds.) EvoWorkshops 2004. LNCS, vol. 3005, pp. 477–488. Springer, Heidelberg (2004)
McCormack, J.: Open problems in evolutionary music and art. In: Rothlauf, F., et al. (eds.) EvoWorkshops 2005. LNCS, vol. 3449, pp. 428–436. Springer, Heidelberg (2005)
McCormack, J.: Facing the future: Evolutionary possibilities for human-machine creativity. In: Machado, P., Romero, J. (eds.) The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music, pp. 417–451. Springer (2008)
McCormack, J.: Creative ecosystems. In: McCormack, J., d’Inverno, M. (eds.) Computers and Creativity, ch. 2, pp. 39–60. Springer, Heidelberg (2012)
McCormack, J.: Aesthetics, art, evolution. In: Machado, P., McDermott, J., Carballal, A. (eds.) EvoMUSART 2013. LNCS, vol. 7834, pp. 1–12. Springer, Heidelberg (2013)
Prusinkiewicz, P., Lindenmayer, A.: The algorithmic beauty of plants. Number xii, 228 in The virtual laboratory. Springer, New York (1990)
Sims, K.: Evolving virtual creatures. In: Computer Graphics, pp. 15–22. ACM SIGGRAPH (July 1994)
