Robots in a Swiss laboratory have evolved to help each other, just as predicted by a classic analysis of how self-sacrifice might emerge in the biological world.
“Over hundreds of generations … we show that Hamilton’s rule always accurately predicts the minimum relatedness necessary for altruism to evolve,” wrote researchers led by evolutionary biologist Laurent Keller of Switzerland’s University of Lausanne in Public Library of Science Biology. The findings were published May 3.
Hamilton’s rule is named after biologist W.D. Hamilton who in 1964 attempted to explain how ostensibly selfish organisms could evolve to share their time and resources, even sacrificing themselves for the good of others. His rule codified the dynamics — degrees of genetic relatedness between organisms, costs and benefits of sharing — by which altruism made evolutionary sense. According to Hamilton, relatedness was key: Altruism’s cost to an individual would be outweighed by its benefit to a shared set of genes.
In some ways, the rule and its accompanying theory of kin selection is contested. Some scientists have used it to extrapolate too easily from insects to people, and some researchers think it overstates the importance of relatedness. But a more fundamental issue with Hamilton’s rule is the difficulty of testing it in natural systems, where animals evolve at a far slower pace than any research grant cycle.
Simulations of evolution in robots, which can “reproduce” in mere minutes or hours, have thus become a potentially useful system for studying evolutionary dynamics. And though simple in comparison to animals, Keller’s group says robot models are not too different from the insects that originally inspired Hamilton.
In the new study, inch-long wheeled robots equipped with infrared sensors were programmed to search for discs representing food, then push those discs into a designated area. At the end of each foraging round, the computerized “genes” of successful individuals were mixed up and copied into a fresh generation of robots, while less-successful robots disappeared from the gene pool.
Each robot was also given a choice between sharing points awarded for finding food, thus giving other robots’ genes a chance of surviving, or hoarding. In different iterations of the experiment, the researchers altered the costs and benefits of sharing; they found that, again and again, the robots evolved to share at the levels predicted by Hamilton’s equations.
“A fundamental principle of natural selection also applies to synthetic organisms,” wrote the researchers. “These experiments demonstrate the wide applicability of kin selection theory.”
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