Evolving novel behaviors via natural selection

Abstract

The traditional fitness function based methodology of artificial evolution is argued to be inadequate for the construction of entities with behaviors novel to their designers. Evolutionary emergence via natural selection (without an explicit fitness function) is the way forward. This paper further considers the question of what to evolve, the focus being on principles of developmental modularity in neural networks. To develop and test the ideas, an artificial world containing autonomous organisms has been created and is described. Results show the developmental system to be well suited to long-term incremental evolution. Novel emergent strategies are identified both from an observer's perspective and in terms of their neural mechanisms. How to Evolve Novel Behaviors The Artificial Life goal presents us with the problem that we do not understand (natural) life well enough to specify it to a machine. Therefore we must either increase our understanding of it until we can, or create a sys...