Skip to Content

Can Robots Really Teach Us About Altruism?

Swiss researchers use real and simulated robots to learn about on an enduring mystery of evolutionary biology.
May 17, 2011

Miniature robots are helping to solve a longstanding biological puzzle–that of altruism.

Why, from a evolutionary biological standpoint, does altruism exist? By a cold Darwinian logic, it shouldn’t: it’s survival of the fittest out there, and how are you going to survive (and thereby pass on your genes) if you keep helping others before yourself?

In the early 1960’s, a scientist named W.D. Hamilton suggested a solution to the riddle, in a paper called “The genetical evolution of social behaviour.” Perhaps it made sense to be altruistic, even from a Darwinian standpoint, with kin who shared a certain amount of genetic material with you. So long as the relationship was close enough, it made evolutionary sense to take one for the team–provided that your teammate was passing along a certain amount of genetic material identical to yours. He even came up with a mathematical equation to describe under what situations altruism was likely to evolve. “Kin selection theory,” the idea is called.

The theory was–and has remained–contentious. The problem is that theories about evolutionary behavior are often hard to test, limited by one small matter: the human lifespan. You can’t exactly hang around for hundreds of generations to see what works, and what doesn’t. You also can’t fine-tune the variables of kinship Hamilton identified, in a living, breathing ecosystem. You can’t play God with nature.

But you can play God with robots. The idea first came to Laurent Keller of the University of Lausanne, Switzerland, according to ScienceNow, to use robots and computers to set up a sort of virtual ecosystem and test whether Hamilton’s theory held. He teamed up with two roboticists at the Ecole Polytechnique Fédérale of Lausanne, Markus Waibel and Dario Floreano, and the three set about designing an experiment.

The team built tiny, simple robots, just a few centimeters tall, made of wheels for mobility and a basic sensory system equipped with a camera. Moving around an arena, they would seek out “food”–small discs scattered by the researchers. To lend a biological flavor to the arena, the team programmed each robot with stream of ones and zeroes that acted as a sort of digital genome.

The researchers found it most practical to then proceed with computerized simulations of the behavior of the actual, physical robots. (They periodically compared the simulated robots’ behavior with that of the physical robots; the comparisons checked out, Floreano told ScienceNow.) The team then introduced a new rule: robots were allowed to share their food with one another, to help ensure that one of their robo-brethren survived to the next generation in lean times. Running the virtual robots through hundreds of generations, they discovered something remarkable: the robots behaved just as Hamilton had predicted species would. Altruism essentially “evolved” among the robots–and when the robots had their digital genome coded to make them closer kin, they evolved altruism all the more rapidly.

The resulting study, “A Quantitative Test of Hamilton’s Rule for the Evolution of Altruism” was recently published in PLoS Biology. The YouTube video below from EPFL further illustrates the experiment.

Some researchers are skeptical however. ScienceNow quotes Harvard’s Martin Nowak as saying the study “tells us nothing about whether Hamilton’s rule makes a correct prediction for actual biological systems.” (Nowak, a biologist, has a horse in this race: he has written in opposition to Hamilton’s rule). Others are much more sanguine. Either way, it’s a novel application of robots and computer simulations to test a longstanding, hotly debated biological theory.

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

The problem with plug-in hybrids? Their drivers.

Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

How scientists traced a mysterious covid case back to six toilets

When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.