Literature DB >> 20583908

Representation invariant genetic operators.

Jonathan E Rowe1, Michael D Vose, Alden H Wright.   

Abstract

A genetic algorithm is invariant with respect to a set of representations if it runs the same no matter which of the representations is used. We formalize this concept mathematically, showing that the representations generate a group that acts upon the search space. Invariant genetic operators are those that commute with this group action. We then consider the problem of characterizing crossover and mutation operators that have such invariance properties. In the case where the corresponding group action acts transitively on the search space, we provide a complete characterization, including high-level representation-independent algorithms implementing these operators.

Mesh:

Year:  2010        PMID: 20583908     DOI: 10.1162/EVCO_a_00007

Source DB:  PubMed          Journal:  Evol Comput        ISSN: 1063-6560            Impact factor:   3.277


  1 in total

1.  How can selection of biologically inspired features improve the performance of a robust object recognition model?

Authors:  Masoud Ghodrati; Seyed-Mahdi Khaligh-Razavi; Reza Ebrahimpour; Karim Rajaei; Mohammad Pooyan
Journal:  PLoS One       Date:  2012-02-27       Impact factor: 3.240

  1 in total

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