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Invariance, self-adaptât ion and correlated mutations in evolution strategies

  • TU Berlin

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25 Citations (Scopus)

Résumé

A conceptual objective behind the self-adaptation of the mutation distribution is to achieve invariance against certain transformations of the search space. In this paper, a priori invariances of a simple evolution strategy and invariances, which can be introduced by self-adaptation, are identified. In principle, correlated mutations can achieve invariance against any linear transformation of the search space. Correlated mutations, as typically implemented, are investigated with respect to both a priori and new invariances. Simulations reveal that neither all a priori invariances are retained, nor the invariance against linear transformation is achieved.

langue originaleAnglais
titreParallel Problem Solving from Nature PPSN VI - 6th International Conference, Proceedings
rédacteurs en chefMarc Schoenauer, Kalyanmoy Deb, Gunther Rudolph, Hans-Paul Schwefel, Xin Yao, Evelyne Lutton, Juan Julian Merelo
EditeurSpringer Verlag
Pages356-364
Nombre de pages9
ISBN (imprimé)9783540410560
Les DOIs
étatPublié - 1 janv. 2000
Modification externeOui
Evénement6th International Conference on Parallel Problem Solving from Nature, PPSN 2000 - Paris, France
Durée: 18 sept. 200020 sept. 2000

Série de publications

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1917
ISSN (imprimé)0302-9743
ISSN (Electronique)1611-3349

Une conférence

Une conférence6th International Conference on Parallel Problem Solving from Nature, PPSN 2000
Pays/TerritoireFrance
La villeParis
période18/09/0020/09/00

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