Deterministic taxonomy based on genetics

By Robin Dowling · 10 months ago

Each evolution is based on a random initial seed. I don't want there to be any preconceived model of the world and the evolution. For this to work, the taxonomy classification has to be a deterministic generalization of an organisms genetics. At all levels of taxonomy, from Domain to Species.

I started building a new Taxonomy class. It's inputs were an array of numbers. Each value representing one component of an organism's genetics. Then the genetics array is transformed and reduced, at different levels of precision for each taxonomy level.

I tried lots and lots of precision settings and transformation methods to find a sweet spot, where I got a reasonable distribution of species based on the variety of the randomly assigned genetics for all the organisms.

This reduction organized organisms into groups of species. But also into fewer groups of genus, family, order, class, phylum, kingdom and domain, all with larger and larger populations for each level of hierarchy. This is still all deterministically grouped, based on randomly assigned genetics.

It was really tricky finding an equilibrium that sorted the sprawling set of organisms and their individually unique set of genetics into groups correctly.

I didn't want to have any special cases where I manually assigned things. The solution had to be a general one for all possible initial random seeds, based only on the input genetics, and the different precisions for each respective taxonomy level.

In the end, the solution was really simple. Just a few lines of math and weights to balance everything.

One Taxonomy algorithm to sort and classify any and all set of randomly assigned compositions of genetics.