The Effect of Multi-Parent Recombination on Evolution Strategies for Noisy Objective Functions

The Effect of Multi-Parent Recombination on Evolution Strategies for Noisy Objective Functions

Yoshiyuki Matsumura (Kobe University, Japan), Kazuhiro Ohkura (Kobe University, Japan) and Kanji Ueda (Kobe University, Japan)
Copyright: © 2003 |Pages: 17
DOI: 10.4018/978-1-59140-037-0.ch015
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Abstract

In this chapter we apply (m / m, l)-ES to noisy test functions, in order to investigate the effect of multi-parent versions of both intermediate recombination and discrete recombination. Among the many formulations of ES, we test three in particular; Classical-ES (CES), i.e., Schwefel’s original ES (Schwefel, 1995, Bäck, 1996); Fast-ES (FES), i.e., Yao and Liu’s extended ES (Yao & Liu, 1997); and Robust-ES (RES), i.e., our extended ES (Ohkura, 2001). Computer simulations are used to compare the performance of multi-parent versions of intermediate recombination and discrete recombination in CES, FES and RES. We saw that the performance of the (m / m, l)-ES algorithms depended on the particular objective functions. However, the FES and RES algorithms were seen to be improved by multi-parent versions of discrete recombination applied to both object parameters and strategy parameters.

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Table of Contents
Preface
Masoud Mohammadian, Rahul A. Sarker, Xin Yao
Chapter 1
Yong Liu, Xin Yao, Tetsuya Higuchi
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Chapter 2
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A Perturbation Size-Independent Analysis of Robustness in Neural Networks by Randomized Algorithms
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Chapter 4
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Chapter 5
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Chapter 6
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Chapter 7
M. Mohammadian
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Chapter 8
D. C. Panni, A. D. Nurse
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Chapter 13
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Chapter 15
Yoshiyuki Matsumura, Kazuhiro Ohkura, Kanji Ueda
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The Effect of Multi-Parent Recombination on Evolution Strategies for Noisy Objective Functions
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Chapter 16
J.-L. Fernandez-Villacanas Martin, P. Marrow, M. Shackleton
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Chapter 17
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