Reducing the arity in unbiased black-box complexity

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Abstract

We show that for all 1 k d log n the k-ary unbiased black-box complexity of the n-dimensional OneMax function class is O(n/k). This indicates that the power of higher arity operators is much stronger than what the previous O(n/log k) bound by Doerr et al. (Faster black-box algorithms through higher arity operators, Proc. of FOGA 2011, pp. 163 - 172, ACM, 2011) suggests. The key to this result is an encoding strategy, which might be of independent interest. We show that, using k-ary unbiased variation operators only, we may simulate an unrestricted memory of size O(2 k) bits.

Original languageEnglish
Title of host publicationGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation
Pages1309-1316
Number of pages8
DOIs
Publication statusPublished - 13 Aug 2012
Externally publishedYes
Event14th International Conference on Genetic and Evolutionary Computation, GECCO'12 - Philadelphia, PA, United States
Duration: 7 Jul 201211 Jul 2012

Publication series

NameGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation

Conference

Conference14th International Conference on Genetic and Evolutionary Computation, GECCO'12
Country/TerritoryUnited States
CityPhiladelphia, PA
Period7/07/1211/07/12

Keywords

  • black-box complexity
  • running time analysis
  • theory

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