Evolving Fractal Drawings
Inhaltsverzeichnis
Reference
Jon Bird: Evolving Fractal Drawings. In: Generative Art 2006.
DOI
Abstract
We are using an evolutionary robotics approach to generate minimal models of creativity. Our preliminary simulation results demonstrate that this methodology can produce robots that mark their environments and interact with the lines that they have made. These simulated robots possess a ‘no strings attached’ form of agency and some of their behaviour can be described as novel relative to their individual behavioural histories and to the behaviours of other members of the evolving population. Arguably, they thus satisfy two conditions necessary for creativity: agency and novelty. Open questions remain: Are the robots’ behaviours creative? Will they become creative as we incrementally increase the complexity of the robot controllers? Can their mark making be classified as drawing?
A number of common criticisms of the project fall under the broad category of value. In the preliminary model the robots neither evaluate the process nor the product of mark making. The robots can only detect the presence of a mark in a 2mm x 2mm region underneath them. How could an agent, from such a ‘myopic’ viewpoint, have any sense of the global pattern of the marks made across a large arena? And how could such agents have any sense of when to stop? Finally, the present results fall short of our artistic goal of producing a gallery exhibit, since currently the products of these robots are unlikely to engage audiences (without considerable knowledge of the methodology involved).
Here we outline a fractal framework that addresses each of these concerns: our robots will be endowed with a ‘fractal detector’; and they will acquire fitness for making marks with a self-similar structure. The robots will be able to interact with their products in a way that involves a kind of judgment of the product as it is being produced. Although their viewpoint will still be limited to a local region, the robots will be able to generate a coherent self-similar pattern across the arena without requiring a global perspective mechanism, such as a bird’s-eye view camera or topographic memory. The framework will also provide a natural finishing criterion: once a self-similar pattern covers the arena the robots will no longer make marks. Finally, fractal images do engage people. And knowledge that these agents have a ‘fractal preference’ should enhance that engagement, since audiences will be able to watch the development of a global self-similar pattern through the simultaneous mark making of a group of robots.
Extended Abstract
Bibtex
Used References
[1] J. Bird, D. Stokes, P. Husbands, P. Brown and B. Bigge, Towards Autonomous Artworks. Leonardo Electronic Almanac, 2007 (in press).
[2] J. Bird and D. Stokes, Evolving Minimally Creative Robots. In S. Colton and A. Pease (Eds.) Proceedings of The Third Joint Workshop on Computational Creativity (ECAI '06), 1 - 5, 2006.
[3] M. A. Boden, The Creative Mind. Routledge, 2004.
[4] B. B. Mandelbrot, The Fractal Geometry of Nature, W.H. Freeman and Company, 2007.
[5] R. P. Taylor, Fractal expressionism - where art meets science. In J. Casti and A. Karlqvist (Eds.) Art and Complexity, Elsevier Press, 2003. http://pages.uoregon.edu/msiuo/taylor/human_response/Pollock(FractalExpressionism2003).pdf
[6] D.Floreano, P. Husbands, S. Nolfi, Evolutionary Robotics. In B. Sicilianoand O. Khatib (Eds.) Springer Handbook of Robotics, Chapter 63, Springer, 2007 (in press).
[7] T.M.C. Smith, P. Husbands, A. Philippides and M. O'Shea, Neuronal plasticity and temporal adaptivity: GasNet robot control networks. Adaptive Behavior, 10(3/4), 161-184, 2002.
Links
Full Text
http://www.generativeart.com/on/cic/papersGA2006/48.htm
