Cultural Evolution in a Population of Neural Networks

Abstract

Genetic algorithms are computational models of die evolution of good solutions to problems based on the selective reproduction of the best variants and the constant addition of random variability to the population of variants. In biological evolution variants are inherited genotypes that are transmitted from parents to offspring. In cultural evolution behavioral variants are trasmitted from one individual to another because one individual (the learner) imitates another individual (the teacher). If the two individuals belong to successive generations, reproduction of teachers is selective, and random noise in added to the cultural transmission of behaviors from teachers to learners, good solutions to problems can evolve by cultural rather than biological evolution.