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Evolutionary Games

  • Reference work entry
Encyclopedia of Machine Learning

  • 188 Accesses

Definition

Evolutionary algorithms are a family of algorithms inspired by the workings of evolution by natural selection, whose basic structure is to

  1. 1.

    Produce an initial population of individuals, these latter being candidate solutions to the problem at hand

  2. 2.

    Evaluate the fitness of each individual in accordance with the problem whose solution is sought

  3. 3.

    While termination condition not met do

    1. a.

      Select fitter individuals for reproduction

    2. b.

      Recombine (crossover) individuals

    3. c.

      Mutate individuals

    4. d.

      Evaluate fitness of modified individuals

  4. 4.

    End while

Evolutionary games is the application of evolutionary algorithms to the evolution of game-playing strategies for various games, including chess, backgammon, and Robocode.

Motivation and Background

Ever since the dawn of artificial intelligence in the 1950s, games have been part and parcel of this lively field. In 1957, a year after the Dartmouth Conference that marked the official birth of AI, Alex Bernstein designed a program for...

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Recommended Reading

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Author information

Authors and Affiliations

    Authors
    1. Moshe Sipper
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    Editor information

    Editors and Affiliations

    1. School of Computer Science and Engineering, University of New South Wales, Sydney, Australia, 2052

      Claude Sammut

    2. Faculty of Information Technology, Clayton School of Information Technology, Monash University, P.O. Box 63, Victoria, Australia, 3800

      Geoffrey I. Webb

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    © 2011 Springer Science+Business Media, LLC

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    Sipper, M. (2011). Evolutionary Games. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_282

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