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Book Chapter
Mutate large, but inherit small! On the analysis of rescaled mutations in (
[1\tilde],[(
l
)\tilde]
\tilde 1,\tilde \lambda
)-ES with noisy fitness data
Book Series
Lecture Notes in Computer Science
Publisher
Springer Berlin / Heidelberg
ISSN
0302-9743 (Print) 1611-3349 (Online)
Volume
Volume 1498/1998
Book
Parallel Problem Solving from Nature — PPSN V
DOI
10.1007/BFb0056843
Copyright
1998
ISBN
978-3-540-65078-2
DOI
10.1007/BFb0056854
Pages
109-118
Subject Collection
Computer Science
SpringerLink Date
Tuesday, August 01, 2006
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Mutate large, but inherit small! On the analysis of rescaled mutations in (
)-ES with noisy fitness data
Hans-Georg Beyer
1
(1)
Department of Computer Science XI, University of Dortmund, D-44221 Dortmund, Germany
Abstract
The paper presents the asymptotical analysis of a technique for improving the convergence of evolution strategies (ES) on noisy fitness data. This technique that may be called “Mutate large, but inherit small”, is discussed in light of the EPP (evolutionary progress principle). The derivation of the progress rate formula is sketched, its predictions are compared with experiments, and its limitations are shown. The dynamical behavior of the ES is investigated. It will be shown that standard self-adaptation has considerable problems to drive the ES in its optimum working regime. Remedies are provided to improve the self-adaptation.
Hans-Georg
Beyer
Email:
beyer@ludo.cs.uni-dortmund.de
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Referenced by
2 newer articles
Johansson, Anders M. (2009) .
IEEE Transactions on Evolutionary Computation
13(4)
[CrossRef]
Arnold, Dirk V. (2007) .
IEEE Transactions on Evolutionary Computation
11(4)
[CrossRef]
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