Does evolution favor simple algorithms?

Symmetry abounds in nature, often in its most beautiful forms. A perfect snowflake, a blooming sunflower, a light-harvesting complex of a bacterium– they all feature a striking symmetry, shaped by a grander design.

But how was this design born? Why have so many natural forms manifested in such ordered patterns, especially when the laws of thermodynamics dictate that the universe is trending toward higher entropy and ever-increasing randomness?

Could it be that evolution favors symmetry? Scientists think so, and a team of researchers from a Norwegian university set out to prove why. In one report published in the Proceedings of the National Academy of Sciencesthe team combined elements of biology, computer science and mathematics to support the theory that evolution has an overwhelming preference for ‘simple’ algorithms, which determine how our planet’s natural structures flourish .

Such algorithms encode the building blocks of all life on Earth, from the mitochondrial cells of a leopard’s muscle fibers to the chloroplasts of an aspen, all of which are remarkably symmetrical. The simpler these algorithms are, the better, scientists say, because the more complexity presents the greater chance of things going wrong.

And symmetry, they say, is simpler: “Symmetrical phenotypes generally need less information to code algorithmically, due to subunit repetition,” the paper says.

In other words, as the study’s lead author, Iain Johnston, Explain“Imagine having to tell a friend how to tile a floor using as few words as possible. . . You wouldn’t say: put diamonds here, long rectangles here, wide rectangles here. You would say something like: put square tiles everywhere. And this simple and easy recipe yields a highly symmetrical result. As a result, there is an abundance of symmetry in tile patterns all over the world – and in nature, whether radial (starfish, pine cones, cross section of a kiwi) or bilateral (a butterfly, a maple leaf).

The team used computer modeling to show that many more possible genomes in life describe simple than complex algorithms, and eventually simpler algorithms are likely to be discovered by evolution. They then rooted these findings in the field of algorithmic information theory, “which provides quantitative predictions for the bias toward descriptive simplicity,” says Ard Louis, a professor at the University of Oxford and corresponding author of the book. ‘study.

In a final setting, the authors relate these findings to the “famous trope of monkeys randomly typing on typewriters.” Called the “Infinite Monkey Theorem,” this thought experiment posits that a monkey hitting random keys on a typewriter for an infinite amount of time will eventually produce a given text, like the complete works of William Shakespeare, among literally all other literature. imaginable. But instead, think of these texts as algorithms, and the monkey as nature’s programmer, embodying the hissing forces of physics and the very state of being. Monkeys more frequently produced simple than complex algorithms, simply by virtue of probability. That, say the scientists, is a more intuitive way to think about it.

In the future, the team hopes to study their predictions of how a bias for simple algorithms shapes larger-scale development processes.

Sharon D. Cole