Representation Invariant Genetic Operators
Author(s) -
Jonathan E. Rowe,
Michael D. Vose,
Alden H. Wright
Publication year - 2010
Publication title -
evolutionary computation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.732
H-Index - 82
eISSN - 1530-9304
pISSN - 1063-6560
DOI - 10.1162/evco_a_00007
Subject(s) - crossover , invariant (physics) , mathematics , representation (politics) , set (abstract data type) , action (physics) , theoretical computer science , algebra over a field , computer science , pure mathematics , artificial intelligence , physics , quantum mechanics , politics , political science , law , mathematical physics , programming language
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.
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