I've been thinking about minimal models of evolution. I concluded that you need information to be copied with some transformation, some death, and a way for the information in question to encode its ability to avoid death.
In trying to simulate that, neural networks were a good fit since they are universal function solvers. I definitely took some inspiration from NEAT[0], though I'm not using any form of crossover.
I've been thinking about minimal models of evolution. I concluded that you need information to be copied with some transformation, some death, and a way for the information in question to encode its ability to avoid death.
In trying to simulate that, neural networks were a good fit since they are universal function solvers. I definitely took some inspiration from NEAT[0], though I'm not using any form of crossover.
AMA
[0] https://en.wikipedia.org/wiki/Neuroevolution_of_augmenting_t...