Structural Search Spaces and Genetic Operators

In a previous paper (Rowe et al., 2002), aspects of the theory of genetic algorithms were generalised to the case where the search space, , had an arbitrary group action defined on it. Conditions under which genetic operators respect certain subsets of were identified, leading to a generalisation of the termschema. In this paper, search space groups with more detailed structure are examined. We define the class of structural crossover operators that respect certain schemata in these groups, which leads to a generalised schema theorem. Recent results concerning the Fourier (or Walsh) transform are generalised. In particular, it is shown that the matrix group representing can be simultaneously diagonalised if and only if is Abelian. Some results concerning structural crossover and mutation are given for this case.

[1]  Alden H. Wright,et al.  The Simple Genetic Algorithm and the Walsh Transform: Part I, Theory , 1998, Evolutionary Computation.

[2]  Alden H. Wright,et al.  Group Properties of Crossover and Mutation , 2002, Evolutionary Computation.

[3]  Christopher R. Stephens,et al.  Schemata Evolution and Building Blocks , 1999, Evolutionary Computation.

[4]  D. E. Goldberg,et al.  Genetic Algorithms in Search , 1989 .

[5]  Michael D. Vose,et al.  The simple genetic algorithm - foundations and theory , 1999, Complex adaptive systems.

[6]  Michael D. Vose Determining concepts by group membership , 2005, Applicable Algebra in Engineering, Communication and Computing.

[7]  Alden H. Wright,et al.  Implicit Parallelism , 2003, GECCO.

[8]  R. Tennant Algebra , 1941, Nature.

[9]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[10]  Nicholas J. Radcliffe,et al.  The algebra of genetic algorithms , 1994, Annals of Mathematics and Artificial Intelligence.

[11]  Siddhartha Bhattacharyya,et al.  General Cardinality Genetic Algorithms , 1997, Evolutionary Computation.

[12]  A. Wright,et al.  Form Invariance and Implicit Parallelism , 2001, Evolutionary Computation.

[13]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[14]  D. E. Goldberg,et al.  Genetic Algorithms in Search, Optimization & Machine Learning , 1989 .