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.
|Title of host publication||The Seventh White House Papers: Graduate Research in the Cognitive Computing Sciences at Sussex|
|Editors||Peter de Bourcier, Ronald Lemmen, Adrian Thompson|
|Publisher||University of Sussex|
|Publication status||Published - 1995|