This crate is supposed to act as the representation/reproduction aspect in neuroevolution algorithms and may be combined with arbitrary selection mechanisms.
SET stands for Set Encoded Topology and this crate implements a genetic data structure, the Genome,
using this set encoding to describe artificial neural networks (ANNs).
Further this crate defines operations on this genome, namely Mutations and Crossover.
Mutations alter a genome by adding or removing genes, crossover recombines two genomes.
To have an intuitive definition of crossover for network structures the NEAT algorithm defined a procedure and has to be understood as a mental predecessor to this SET encoding,
which very much is a formalization and progression of the ideas NEAT introduced regarding the genome.
The thesis describing this genome and other ideas can be found here, a paper focusing just on the SET encoding will follow soon.
[dependencies]
set_genome = "0.1"See the documentation more information.