Coevolutionary species adaptation genetic algorithms: growth and mutation on coupled fitness landscapes

摘要

The species adaptation genetic algorithm (SAGA) was introduced to facilitate the open-ended evolution of artificial systems. The approach enables genotypes to increase in length through appropriate mutation operators. Most recently, this has been undertaken within coevolutionary or multi-agent scenarios. This paper uses the abstract NKCS model of coevolution to examine the behaviour of SAGA on fitness landscapes which are coupled to those of other evolving entities to varying degrees. Results indicate that the rate of genome growth is affected by the degree of coevolutionary interdependence between the entities and that the mutation rate is critical within such systems.