Starting with another relatively light generative project, this project was done as a Halloween present for the creator’s children. The monsters were created by algorithmically placing “monster bits” like tentacles and eyeballs from a kit of parts. This is an extremely straightforward application of generative programming, but one that is quite appealing to me. The graphics used here are pleasant but not particularly inspired, but I could see a similar system being used to create some really inspirational stuff. For example, generating silhouettes for Monster designs based on a given physiological feature (Make me some tentacle monsters, some quadrupeds, some stuff with shells, etc).
Evolution picks up on the trail blazed by many of the genetic algorithms we discussed in class, specifically Ludivine Lechat’s Graphical Cellular Domestication. The program creates organisms from a template, assigning each various properties based on each creature’s taxonomy. Each creature can then go on to mate and predate, passing on its computational DNA to future generations. The notion of dynamically generating creatures is very appealing to me from a purely aesthetic view, while the notion that physical characteristics and inherited data can affect their behavior makes this sort of project highly compelling.
Simple concept, elegant execution. Cell-F essentially takes data from the classic Game of Life program and stacks results from each generation vertically. When these points are translated into 3D volumes, they take on a sort of eerie hybrid of the orthogonal and biological.