Modeling interactions between filial imprinting and a predisposition using genetic algorithms and neural networks

摘要

I present a neural network model of the complex interactions between filial imprinting and a naive preference for heads and necks in domestic chicks. The fixed weights in the network were evolved in a genetic algorithm simulation which emphasized the survival value of both innate and learned information: having the networks recognize their "mothers". The architecture and genetic algorithm regimen were able to produce five different behaviors exhibited by chicks in laboratory experiment emulations dissimilar to the training regimen used in the genetic algorithm simulations.