The viewers at this exhibit can observe a computer-simulated evolution in progress: an evolution of images. But in this evolution, the viewers are not just observes: they cause the evolution and direct its course.
A population of images is displayed by the computer on an arc of 16 video screens. The viewers determine which images will survive by standing on sensors in front of those they think are the most aesthetically interesting. The pictures that are not selected are removed and replaced by offspring from the surviving images. The new images are copies and combinations of their parents, with various alterations. This is an artificial evolution in which the viewers themselves interactively determine the "fitness" of the pictures by standing on the related sensors. As the cycle continues, the viewers of this simulated evolution collectively determine the pathway to previously unseen populations of pictures.
And analogy can be made between these images and biological organisms. The are both synthesized from "genetic" descriptions and are both subjected to the forces of evolution. An organism is grown from the coded instructions of its DNA. Similarly, these images are generated from the coded instructions of its DNA. Similarly, these images are generated from instructions in the form of computer coded mathematical eequations. The computer code (or DNA) is the genotype, and the resulting imges (or organism) is the phenotype.
When one or more of these images are chosen for survival, they reproduce by copying and combining their genetic descriptions, often acquiring some random mutations in the process. The new genetic descriptions produce offspring images that look similar to their parents, but often have significant alterations. Some mutations can increase the complexity of the genetic descriptions and cause the resulting images to increase in visual complexity. Complex equations can sometimes evolve that would be quite difficult for any human to design or even understand.
During die course of exhibit, the computer remembers those images that hive been chosen multiple times by the viewers. Upon request, the computer can recall these previous favorits and continue evolving them. In this way, visitors can start the evolutionary process at points where visitors from previous days left off. In addition, the best results from different evolutions can be combined to further generate new breeds of images. This permits the collective evolution of a larger population of images, which all visitors can contribute to and improve upon, throughout the entire period of the installation.
At any time, the viewers can ales request the computer to start over and begin a new evolution from scratch. In this case, the computer generates an initial population of fairly simple images from brief, randomly assembled genetic descriptions. The viewers then choose which of these will reproduce, and the evolution proceeds.
