A game-theoretic approach for designing mixed mutation strategies

Jun HE, Xin YAO

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

16 Citations (Scopus)


Different mutation operators have been proposed in evolutionary programming. However, each operator may be efficient in solving a subset of problems, but will fail in another one. Through a mixture of various mutation operators, it is possible to integrate their advantages together. This paper presents a game-theoretic approach for designing evolutionary programming with a mixed mutation strategy. The approach is applied to design a mixed strategy using Gaussian and Cauchy mutations. The experimental results show the mixed strategy can obtain the same performance as, or even better than the best of pure strategies. © Springer-Verlag Berlin Heidelberg 2005.
Original languageEnglish
Title of host publicationAdvances in Natural Computation : First International Conference, ICNC 2005, Changsha, China, August 27-29, 2005, Proceedings, Part III
EditorsLipo WANG, Ke CHEN, Yew Soon ONG
PublisherSpringer Berlin Heidelberg
Number of pages10
ISBN (Electronic)9783540318637
ISBN (Print)9783540283201
Publication statusPublished - 2005
Externally publishedYes

Publication series

NameLecture Notes in Computer Science
PublisherSpringer, Berlin, Heidelberg
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


  • Mutation Operator
  • Mixed Strategy
  • Pure Strategy
  • Evolutionary Game Theory
  • Mutation Strategy


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