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Comment by hirundo

Here's [0] the conclusion of a paper on optimizing population sizes in genetic algorithms:

> The use of smaller populations result in lower accuracy of the solution, obtained for a smaller computational time. The further increase of the population size increases the accuracy of solution. This effect is observed to a population size of 100 chromosomes. The use of larger populations does not improve the solution accuracy and only increase the needed computational resources.

The same effect may be what this article is describing, applied to culture. As the audience grows, the neural resources applied to judgement grow, but after a point the accuracy does not. A larger population does not translate into a more thorough search of the solution space compared to the same population divided into smaller niches that do not communicate.

I doubt it would be a great improvement to divide the population back down to the tiny tribes of prehistory, but the optimum is likely somewhere between that and our global melting pot.

Inclusion is a modern creed and battle cry, but to a point exclusion also has its place in increasing innovation, in that it creates independent niches that each attempt to climb different maxima.

[0] https://annals-csis.org/proceedings/2013/pliks/167.pdf

parent hirundo 7 years ago

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