Genetic algorithms in evolutionary modelling

Evolutionary modellers have recently taken an interest in the use of computer simulations based on genetic algorithms; this paper offers two contributions to this literature. In the initial sections we aim to place the GA into a general review of evolutionary dynamics, including Fisher's Principle. In the second half of the paper, we offer a modified GA that replaces the selection and crossover operators with a selective transfer operator. We argue this modified algorithm has a ready interpretation in the modelling of learning, namely as a proxy for imitation in a population working with modular technologies. A simple application is used to give an initial assessment of the algorithm and to test Fishes's Principle.