On the design of an artificial life simulator

Abstract

This paper describes the design of an artificial life simulator. The simulator uses a genetic algorithm to evolve a population of neural networks to solve a presented set of problems. The simulator has been designed to facilitate experimentation in combining different forms of learning (evolutionary algorithms and neural networks). We present results obtained in simulations examining the effect of individual life-time learning on the population's performance as a whole.