What survival of the fittest actually means

Darwin did not coin the phrase and came to regret adopting it. It is responsible for more misunderstanding of evolution than any other five words, because both halves mislead: "fittest" does not mean strongest, and "survival" is not the thing being selected for.

Background concept

What fitness actually refers to

Fitness in evolutionary biology means one thing: how many descendants you leave. Not health, not strength, not speed, not complexity, not sophistication. An organism that is weaker, slower and shorter-lived than its rival but leaves more surviving offspring is fitter, by definition, and the definition is the whole point.

This makes the famous phrase close to circular, and the circularity is not a flaw in evolution - it is a flaw in the phrase. "The ones that leave more descendants leave more descendants" is trivially true. The substantive claim is different and much more interesting: heritable differences in descendant-leaving accumulate, so a population changes over generations in a direction nothing chose.

A world with no fitness function at all

Most artificial evolution has a fitness function: a number the researcher writes down that says what counts as good. Creatures are scored, the high scorers are bred, and the population improves at the thing in the formula. That is a powerful tool and it is not what happens in nature, because nature has no formula.

This project's world has no fitness function. Nothing is scored. Nothing is bred by an outside hand. An organism has offspring if it is alive, has enough energy, and circumstances allow. Whatever "fitter" means here is not written anywhere - it is whatever is actually happening, and the only way to find out is to measure which lines persisted.

That absence has a consequence worth sitting with. When a family line here takes over the population, nobody can tell you what it was better at, because no quantity was being optimised. You can measure that it won. Explaining why is a separate and much harder job, and often it cannot be done honestly at all.

A real case, including the part that cannot be settled

In this world's first universe, one family line went from ten members to the entire population in roughly fifty thousand ticks, carrying a movement direction nothing had carried before. It is tempting to say its direction was advantageous. The measurement does not support that: the whole population was in sustained decline through the same window, and a line that sweeps during a crash may be a winner or may be the last one standing.

Both readings remain open, and this project publishes it that way rather than choosing the better story. That is what the absence of a fitness function costs you, and it is the same cost biologists pay in the field.

A better phrase

"Differential reproductive success of heritable variants" is accurate, unmemorable, and says exactly what happens. If you want five words, "whatever persists, persists" is closer to the truth than "survival of the fittest" - and it makes clear that evolution is not a competition anybody is judging.

Is evolution random? · Fitness landscapes · A world with nothing being maximised

A curve rising from near zero at tick 680,000 to 100 per cent by tick 775,000, showing the share of Universe 1's living population descended from a single family line.
One family line going from ten members to the whole world in about fifty thousand ticks. It is the clearest case of differential reproductive success this project has recorded, and nobody can say what it was better at, because nothing here was being optimised.

References and further reading

Primary sources for the claims on this page. Where this project's own results are referred to, they link to the page carrying the evidence instead.

  1. Gould, S. J., & Lewontin, R. C. (1979). The spandrels of San Marco and the Panglossian paradigm. Proceedings of the Royal Society B, 205(1161), 581-598. doi:10.1098/rspb.1979.0086
  2. Kimura, M. (1968). Evolutionary Rate at the Molecular Level. Nature, 217, 624-626. doi:10.1038/217624a0
  3. Lenski, R. E., Ofria, C., Pennock, R. T., & Adami, C. (2003). The evolutionary origin of complex features. Nature, 423, 139-144. doi:10.1038/nature01568
  4. Lehman, J., Clune, J., Misevic, D., et al. (2020). The Surprising Creativity of Digital Evolution. Artificial Life, 26(2), 274-306. doi:10.1162/artl_a_00319