Mass extinctions can accelerate evolution: Study

Looking at how robots evolve after a virtual mass extinction modeled after real-life disasters such as the one that killed off the dinosaurs, researchers have found that these catastrophic events may actually speed up evolution by unleashing new creativity in adaptations.

"Focused destruction can lead to surprising outcomes," said one of the researchers Miikkulainen, professor of computer science at The University of Texas at Austin.

"Sometimes you have to develop something that seems objectively worse in order to develop the tools you need to get better," Miikkulainen noted.

In biology, mass extinctions are known for being highly destructive, erasing a lot of genetic material from the tree of life.

But some evolutionary biologists hypothesise that extinction events actually accelerate evolution by promoting those lineages that are the most evolvable, meaning ones that can quickly create useful new features and abilities.

The new study found that, at least with robots, this is the case.

For years, computer scientists have used computer algorithms inspired by evolution to train simulated robot brains, called neural networks, to improve at a task from one generation to the next.

In computer simulations, Miikkulainen and colleagues connected neural networks to simulated robotic legs with the goal of evolving a robot that could walk smoothly and stably.

After several cycles of evolution and virtual extinction, they discovered that the lineages that survived were the most evolvable and, therefore, had the greatest potential to produce new behaviours.

Not only that, but overall, better solutions to the task of walking were evolved in simulations with mass extinctions, compared with simulations without them.

Practical applications of the research could include the development of robots that can better overcome obstacles such as robots searching for survivors in earthquake rubble, exploring Mars or navigating a minefield.

The study was published in the journal PLOS One.