If you ever wondered what it looks like when QWOP-like figures learn to walk through mutation as dictated by a simplified genetic algorithm, here’s your answer. Rafael Matsunaga made a simulation that starts with a bunch of walkers, and the one that stays upright the longest moves on to the next generation. Adjust the probability of mutation and the amount, and there’s a chance the next generation of walkers could go further.

See also genetic algorithm cars. Same idea but with blocky car-like figures. [via kottke]