Dynamic fitness landscapes
Seth Bullock · ePrints Soton (University of Southampton) · 1995
Genetic Algorithms (GAs) are typically thought to work on static fitness landscapes. In contrast, natural evolution works on fitness landscapes that change over evolutionary time as a result of co-evolution. Sexual selection and predator-prey evolution are examined as clear examples of phenomena that transform fitness landscapes. The concept of co-evolution is subsequently defined, before attempts to utilise co-evolution in the use of GAs as design tools are reviewed and speculations concerning future applications of automatic co-evolutionary techniques for design are considered.