Hello. What makes the HyperNEAT approach a breakthrough is its use of a generative encoding based on concepts from developmental biology. Please see my comment one ply deeper in this thread for more information. I encourage you to check out the HyperNEAT publications in order to see why this is very powerful and new technology. Best, Jeff Clune, Postdoctoral Scientist, Michigan State University

Hello- I posted this in reply to another comment, but it is relevant to this thread as well. The HyperNEAT technology is actually cutting-edge, and represents a major innovation versus previous neuroevolution techniques. One major thing that differentiates it from previous evolution of ANNs is that HyperNEAT is based on concepts from developmental biology. Specifically, it evolves compositions of geometric coordinate frames that are abstractions of the diffusing chemical gradients of developing embryos. These concepts enable the evolution of regular patterns in neural wiring that have not been seen before in neuroevolution (see, for example, the pictures of evolved brains in my dissertation, which is available at my website: www.msu.edu/~jclune). The ability to generate regular wiring patterns enables evolution to search in a small search space of short genomes, yet produce functioning brains with millions or more connections. Of course, this article was written for the popular press, so they did not have the ability to get to this level of detail. For those of you that already know a lot about evolutionary computations and neural nets, I encourage you to read the publications about HyperNEAT, either at my website or at those of other researchers using the technology (e.g., the University of Central Florida). I think you'll then be impressed by the breakthroughs in HyperNEAT. You are correct that evolutionary computation itself has been around for a while. But the science described in this article is pushing that technology further. Best, Jeff Clune Postdoctoral Scientist Michigan State University

Hello- The HyperNEAT technology is actually cutting-edge, and represents a major innovation versus previous neuroevolution techniques. One major thing that differentiates it from previous evolution of ANNs is that HyperNEAT is based on concepts from developmental biology. Specifically, it evolves compositions of geometric coordinate frames that are abstractions of the diffusing chemical gradients of developing embryos. These concepts enable the evolution of regular patterns in neural wiring that have not been seen before in neuroevolution (see, for example, the pictures of evolved brains in my dissertation, which is available at my website: www.msu.edu/~jclune). The ability to generate regular wiring patterns enables evolution to search in a small search space of short genomes, yet produce functioning brains with millions or more connections. Of course, this article was written for the popular press, so they did not have the ability to get to this level of detail. For those of you that already know a lot about evolutionary computations and neural nets, I encourage you to read the publications about HyperNEAT, either at my website or at those of other researchers using the technology (e.g., the University of Central Florida). I think you'll then be impressed by the breakthroughs in HyperNEAT. You are correct that evolutionary computation itself has been around for a while. But the science described in this article is pushing that technology further. Best, Jeff Clune Postdoctoral Scientist Michigan State University