Evolutionary robotics
Evolutionary robotics is an embodied approach to Artificial Intelligence AI in which robots are automatically designed using Darwinian principles of natural selection. The positioning of a robot, or a subsystem of a robot such(a) as a neural controller, is optimized against a behavioral goal e.g. run as fast as possible. Usually, designs are evaluated in simulations as fabricating thousands or millions of designs together with testing them in the real world is prohibitively expensive in terms of time, money, as alive as safety.
An evolutionary robotics experiment starts with a population of randomly generated robot designs. The worst performing designs are discarded and replaced with mutations and/or combinations of the better designs. This evolutionary algorithm maintain until a prespecified amount of time elapses or some planned performance metric is surpassed.
Evolutionary robotics methods are especially useful for engineering science machines that must operate in settings in which humans throw limited intuition nanoscale, space, etc.. Evolved simulated robots can also be used as scientific tools to generate new hypotheses in biology and cognitive science, and to test old hypothesis that require experiments that form proven unoriented or impossible to carry out in reality.