OK, so my title was a bit provocative, but here's what I'm going to do for my project (and hopefully it will work). (When we went around on Wednesday and explained our projects, I said basically this, but now I'd like to elaborate it more.) Training Neural Networks to do ANDs and ORs is all fine and good, but I feel that it misses the point, at least in terms of emergence. Neural Networks show great potential in terms of solving computing and AI problems, but I'd like to go somewhere different. I want to write a simulated world where the creatures are run by neural networks. The inputs to the neural networks will be the "sense": vision, for example, could be represented by two parameters: one for the distance of the nearest object in the line of sight, and another one for the "color", where food would have one color, other creatures another color, and obstacles a third. (The distance and color would have to be normalized so as to be a number between zero and one, of course.) The outputs, then, could be actions: one output could be whether to move forward or not, another to be whether to turn left, right, or not at all, and maybe another could be to change the creature's own color.