Much of our work on applications involves neuroevolution of behavior in real-world domains such as control, robotics, game playing, and artificial life, but also design and optimization of wavelets, sorting networks, musical score, proofs, and resource allocations. Other areas include reinforcement learning in robotics, packet routing, and satellite communication, unsupervised learning for pattern recognition and visualization, and supervised learning for applicant evaluation, intrusion detection, and process control.