Approximating the distribution of fitness over hamming regions

Andrew M. Sutton, L. Darrell Whitley, Adele E. Howe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

The distribution of fitness values across a set of states sharply inuences the dynamics of evolutionary processes and heuristic search in combinatorial optimization. In this paper we present a method for approximating the distribution of fitness values over Hamming regions by solving a linear programming problem that incorporates low order moments of the target function. These moments can be retrieved in polynomial time for select problems such as MAX-k-SAT using Walsh analysis. The method is applicable to any real function on binary strings that is epistatically bounded and discrete with asymptotic bounds on the cardinality of its codomain. We perform several studies on the ONE-MAX and MAX-k-SAT domains to assess the accuracy of the approximation and its dependence on various factors. We show that the approximation can accurately predict the number of states within a Hamming region that have an improving fitness value.

Original languageEnglish (US)
Title of host publicationFOGA'11 - Proceedings of the 2011 ACM/SIGEVO Foundations of Genetic Algorithms XI
Pages93-103
Number of pages11
DOIs
StatePublished - May 20 2011
Event11th Foundations of Genetic Algorithms Workshop, FOGA XI - Schwarzenberg, Austria
Duration: Jan 5 2011Jan 9 2011

Publication series

NameFOGA'11 - Proceedings of the 2011 ACM/SIGEVO Foundations of Genetic Algorithms XI

Other

Other11th Foundations of Genetic Algorithms Workshop, FOGA XI
CountryAustria
CitySchwarzenberg
Period1/5/111/9/11

Keywords

  • Pseudo-boolean functions
  • Search space analysis

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