Dynamic fitness landscapes

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)


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.
Original languageUndefined/Unknown
Title of host publicationThe Seventh White House Papers: Graduate Research in the Cognitive Computing Sciences at Sussex
EditorsPeter de Bourcier, Ronald Lemmen, Adrian Thompson
PublisherUniversity of Sussex
Publication statusPublished - 1995

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