Definition
Evolutionary algorithms are a family of algorithms inspired by the workings of evolution by natural selection, whose basic structure is to:
- 1.
Produce an initial population of individuals, these latter being candidate solutions to the problem at hand.
- 2.
Evaluate the fitness of each individual in accordance with the problem whose solution is sought.
- 3.
While termination condition not met do:
- (a)
Select fitter individuals for reproduction
- (b)
Recombine (crossover) individuals
- (c)
Mutate individuals
- (d)
Evaluate fitness of modified individuals
- (a)
- 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...
Recommended Reading
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Hauptman A, Sipper M (2005a) Analyzing the intelligence of a genetically programmed chess player. In: Late breaking papers at the 2005 genetic and evolutionary computation conference (GECCO 2005), Washington, DC
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Sipper, M. (2014). Evolutionary Games. In: Sammut, C., Webb, G. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7502-7_92-1
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DOI: https://doi.org/10.1007/978-1-4899-7502-7_92-1
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