MATURATION AND THE EVOLUTION OF IMITATIVE LEARNING IN ARTIFICIAL ORGANISMS

The traditional explanation of delayed maturation age, as part of an e volved life history, focuses on the increased costs of juvenile mortal ity due to early maturation. Prior quantitative models of these trade- offs, however, have addressed only morphological phenotypic traits, su ch as body size. We argue that the development of behavioral skills pr ior to reproductive maturity also constitutes an advantage of delayed maturation and thus should be included among the factors determining t he trade-off for optimal age at maturity Empirical support for this hy pothesis from animal field studies is abundant This article provides f urther evidence drawn from simulation experiments. Latent energy envir onments (LEE) are a class of tightly controlled environments in which learning organisms are modeled by neural networks and evolve according to a type of genetic algorithm. An advantage of this artificial world is that if becomes possible to discount all nonbehavioral costs of ea rly maturity in order to focus exclusively on behavioral consequences. Despite large selective costs imposed on parental fitness due to prol onged immaturity, the optimal age at maturity is shown to be significa ntly delayed when offspring learn from their parents' behavior via imi tation.