It always felt like there's more potential in this direction. Maybe with a magic sprinkling of neural nets?
The big thing I spent time on was animating cross-fades between evolved expressions. I’ll send a link to the vid & paper if you’re interested.
A web version would make a great time-waster. At least as the author I wound up spending much more time clicking through the space of images than working on the code; it might perhaps not feel as compelling without the feeling of getting something for almost nothing when your own program comes to life.
https://www.youtube.com/watch?v=kLmtvIt6ihA
http://dahart.com/paper/hart_evomusart_2007_paper.pdf
http://dahart.com/paper/hart_evomusart_2007_slides.pdf
BTW, Karl Sims read this paper and recommended it for Siggraph, but a few other reviewers were fairly opposed to generative art papers. C'est la vie.
Slightly related to the starting topic of learned exploits: op_hwb_color() producing most of the colors seems to have suffered from some undefined or implementation-defined behavior -- I couldn't reproduce old pictures when I came back to this many years later. Yet that one misbehavior deserves a lot of the credit for whatever aesthetic value turned up. C'est encore la vie.
To me it sounded like something a referee would request or something they suspected a referee would request.
Many of the projects here are all inspired by Karl Sims' work in the early 90's.
http://www.karlsims.com/
Sims evolved virtual creates by specifying goals to achieve and then running a physics simulation. He noted at the time that the evolution process was great at exploiting bugs in the simulation.
https://www.youtube.com/watch?v=JBgG_VSP7f8
I was insipred enough by Sims' genetic images (http://www.karlsims.com/genetic-images.html) that I spent a few years trying to get surprising and beautiful results of my own, with some limited success (https://flic.kr/s/3Xoz).