A “Noise Gene” for Econets

Genetically controlled noise is applied to the weights of neural networks trained with a genetic algorithm. Networks simulate simple organisms living in an environment Reproduction is based on the ability of each network, during its life, to respond to sensory information from the environment with appropriate motor action. Each network has an amount of noise which is genetically inherited (in the ‘noise gene’) with mutations and it varies interindividually. Noise modifies the value of a weight differently for each spreading of the activation through the network. Such noise has a positive effect on the evolutionary increase in fitness and it makes fitness less dependent on the initial choice of a random population. Evolutionarily, whatever its initial amount, noise reaches an intermediate amount during the first third of the evolutionary process and then it goes near zero.