On the Impact of the Representation on Fitness Landscapes

作者: Paul Albuquerque , Bastien Chopard , Christian Mazza , Marco Tomassini

DOI: 10.1007/978-3-540-46239-2_1

关键词:

摘要: In this paper we study the role of program representation on properties a type Genetic Programming (GP) algorithm. specific case, which believe to be generic standard GP, show that way individuals are coded is an essential concept impacts fitness landscape. We give evidence ruggedness landscape affects behavior algorithm and find that, below critical population, whose size representation-dependent, premature convergence occurs.

参考文章(11)
Raphaël Cerf, The dynamics of mutation-selection algorithms with large population sizes Annales De L Institut Henri Poincare-probabilites Et Statistiques. ,vol. 32, pp. 455- 508 ,(1996)
Paul Albuquerque, Christian Mazza, Mutation-Selection Algorithm: a Large Deviation Approach foundations of genetic algorithms. pp. 227- 240 ,(2001) , 10.1016/B978-155860734-7/50095-0
Wolfgang Banzhaf, Robert E. Keller, Genetic programming using genotype-phenotype mapping from linear genomes into linear phenotypes Proceedings of the 1st annual conference on genetic programming. pp. 116- 122 ,(1996)
David E. Goldberg, Una-May O’Reilly, Where Does the Good Stuff Go, and Why? How Contextual Semantics Influences Program Structure in Simple Genetic Programming european conference on genetic programming. pp. 16- 36 ,(1998) , 10.1007/BFB0055925
Mark Wineberg, Franz Oppacher, A Representation Scheme To Perform Program Induction in a Canonical Genetic Algorithm parallel problem solving from nature. pp. 292- 301 ,(1994) , 10.1007/3-540-58484-6_273
Raphaël Cerf, Asymptotic convergence of genetic algorithms Advances in Applied Probability. ,vol. 30, pp. 521- 550 ,(1998) , 10.1239/AAP/1035228082
Kenneth E Kinnear, Peter J Angeline, None, Advances in Genetic Programming ,(1994)