I’ve been catching up reading AI papers on my Sony Reader, it’s very nice to have all these books and papers with you all the time, and I ran across a paper on 3d creatures that evolve and battle. The software is open source and there is extensive information explaining the project.
I evolve virtual creatures. That is, instead of designing the creatures myself, I let Darwinian evolution do the work for me. Starting with a bunch of completely random creatures, I evaluate them, select the “best” (where the definition of “best” depends on what you are trying to obtain: distance covered, outcome of a fight, etc.), allow these “good” creatures to “reproduce” (that is, generate new creatures based on recombination and mutations of these “good” creatures), and start this cycle again with the new population. After a while, increasingly efficient behaviours appear spontaneously.
Both the morphology (body) and behaviour (neural network) of the creatures are fully evolved: I only specify the evaluation function (that is, how to determine the “score” of a creature), and evolution takes care of the design, slowly turning random creatures into highly efficient machines.
This research builds upon the seminal work of Karl Sims; in fact, this was the first successful reimplementation of Karl Sims’ system. I improved the genetic encoding and the developmental system. I also chose to use standard, McCulloch-Pitts neurons instead of the complex functional neurons used by Sims (which makes the problem harder, but more interesting: creatures can’t rely on complex neurons to directly provide useful behaviours, they need come up with their own coordinated neural systems).
I also managed to evolve “fighting” creatures: creatures evolve to smash each other out. I believe this is a first (previous attempts used simplistic forms of “combat”).