Robots are simply more efficient than humans at certain tasks. They already excel at building cars, exploring distant planets and hunting for explosives, but it turns out that robots might also evolve much faster than their flesh-and-blood counterparts.
Nick Cheney, a Ph.D. student at Cornell University, presented his research at an Inside Cornell lecture on May 21. Cheney has developed a method by which complex computer simulations in a specific virtual environment — robots, by his definition — can evolve from selective pressures, just like animals in nature, but on a timescale of days instead of countless generations.
To demonstrate the technology, Cheney showed how a series of diverse but effective robots spontaneously evolved from a single, inefficient ancestor. He programmed a virtual environment with only one parameter: robots that moved faster would be able to produce more offspring. Therefore, the only selective pressure was speed (in the wild, Cheney compared this behavior to running from predators).
"Nature is amazing in how it designs things," Cheney said. "We want robots to interact with their environments as naturally as animals do." Cheney considers natural selection — the process by which biological organisms survive, reproduce and change over time to better suit their environments — to be a natural algorithm, extremely similar to what engineers use to optimize robots over time.
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