Artistic Evolution

     Last week, we spent the majority of our time attempting to answer a question fundamental to any visual GP project we might end up with: how should we encode the “DNA” of the image to allow for the easy modification, cross-breeding, and mutation that evolution requires? We started on this by creating a program capable of rendering (and subsequently modifying) any number of polygons with some specific characteristics: vertices, size, position, rotation, color, transparency, and layering. With a large enough population of polygons it is possible to accurately represent any given image. This general idea was touched upon by Evolution of the Mona Lisa. Although the author presents it as genetic programming it most certainly is not. Rather, it’s hill climbing; there exists no population (spare one parent and one child) and no breeding or biological diversity occurs. Consequently, the program is perhaps significantly less efficient than an actual GP equivalent would be. While this project is nowhere near we’d like to end up, it seems to serve as a good starting point for tweaking our image DNA and also a good crash course in GP. We believe that if this same problem were to be properly implemented with a large population size featuring mutation and crossover, that desirable results could be obtained significantly faster than with the existing model. This shouldn’t take a lot of time once the DNA framework is finished and it will give us an opportunity to play with genetic programming and create a genetic model good for image manipulation, to become familiar with the cluster, to fine tune our DNA system, and perhaps give us some insight into a future fitness test for our project.

     In discussions about the future of our project, two common themes this week have been the idea of Amazon’s Mechanical Turk – suggested by a classmate – and evolution of art as art. Through extremely preliminary and rough estimates, I’ve determined that if we were to use Mechanical Turk it would cost between $0.0005 and $0.0010 per agent per generation to return viable fitness data. To get usable results, the same images would need to be compared multiple times in order to achieve any sense of objectivity. While the cost may seem miniscule, it quickly adds up; with a population size of 1,000 agents and a total of 100,000 generations, the total cost would be between $500 and $1,000. This means that even if we could secure some amount of funding, we could probably only run the process a single time (and it would take a significant amount of time to get all our data back). This is also running under the presupposition that human input is worthwhile and that humans are capable of distinguishing between such minute differences in visual art, especially at the beginning stages when everything is abstract and, probably, terrible.

     The other idea tossed around was evolution as art. There are many ways that this could be accomplished but one concept was a process similar to the Evolution of Mona Lisa. The idea would be to have an exhibit set up in a gallery consisting of a display, a button, a printer, and a camera. When the button is pressed the camera snaps a picture to serve as our fitness test. Immediately a population is created and outsourced to a cluster to strive towards an acceptable image as quickly as possible (with the Evolution of Mona Lisa this takes around two weeks…we’re hoping GP could optimize it a whole lot more, into the ten minute range with the cluster). While the generations are processed, an interesting visual presentation is shown on the screen and the viewer is able to see their image evolve from something completely random and purposeless, purpose to a very deep and philosophical Sagan-esque monologue about the wonder of nature as a computer. At the end of the presentation when the final image is ready, it’s displayed on screen and the viewer is given a series of print outs: the original image, the final image, a timeline of evolution (maybe best image every thousand generations?), and perhaps their final image’s DNA. While the display is not in the process of a presentation it could cycle through previously completed images and display them to the entire gallery. If we were able to present this in a way that highlighted how cool evolution really is while still being aesthetically interesting and dynamic, I think we could create human competitive art; it’s definitely something that would catch my eye at a gallery. Also I’m a nerd so my opinion on the matter of what’s interesting in a gallery could be completely invalid.

This entry was posted on October 13, 2009 at 11:39 pm and is filed under Uncategorized.