Chief Delphi - Autonomous mode... to the max

Congrats on learning enough about neural networks (NN) to want to use them on your robot. I've done quite a bit of research with NNs and genetic algorithms (GA). The life simulator that you describe is actually a fairly common thing when studying NN and GA. Each NN is described by a sequence of DNA. The GA breeds these DNA sequences and only selects the best to continue breeding. The GA is a technique to train the NN. The main problem with controlling your robot with a NN is the size that will be needed(I will explain this later) to process all of the data that your sensors collect. The GA is a hueristic search that will eventually find the correct NN. However, a bad NN could easily cause your robot to damage itself during its training.

Since a feedforward NN basically boils down to a long polynomial function of the inputs, there is no fancy mystery about how it works. Each layer of the network will divide the range of inputs into two groups, on and off. Hundreds of layers are needed to process the hundreds of pixels from a camera.

Thats all I have time for now, but I would be happy to discuss and argue about NN, GA, and artificial intelligence.

P.S. If I havent convinced you to stop using neural networks on your robot, let me know because I would love to help you to succeed despite my predictions. Plus, I had the same dream during my first year at FIRST