The effects of lifetime learning on the diversity and fitness of populations

Evolutionary learning refers to the process whereby a population of organisms evolves, or learns, by genetic means through a Darwinian process of iterated selection and reproduction of fit individuals. Hinton and Nowlan employed a genetic algorithm to study the effects of lifetime learning on the performance of genetic evolution [1]. Each agent in the model possesses a genome, comprised of a string of characters which can be one of 1, 0 or ?. Each agent is allowed a number of rounds of lifetime learning where for each ? in the genotype they ‘guess’ its value, assigning it either a 1 or a 0. Experimental results showed that, once learning was applied, the population converged on the problem solution, showing that individual learning is capable of guiding genetic evolution.