Recombination for learning strategy parameters in the MO-CMA-ES

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Standard

Recombination for learning strategy parameters in the MO-CMA-ES. / Voß, Thomas; Hansen, Nikolaus; Igel, Christian.

Evolutionary Multi-Criterion Optimization: 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009. Proceedings. red. / Matthias Ehrgott; Carlos M. Fonseca; Xavier Gandibleux; Jin-Kao Hao; Marc Sevaux. Springer, 2009. s. 155-168 (Lecture notes in computer science, Bind 5467).

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Harvard

Voß, T, Hansen, N & Igel, C 2009, Recombination for learning strategy parameters in the MO-CMA-ES. i M Ehrgott, CM Fonseca, X Gandibleux, J-K Hao & M Sevaux (red), Evolutionary Multi-Criterion Optimization: 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009. Proceedings. Springer, Lecture notes in computer science, bind 5467, s. 155-168, 5th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2009, Nantes, Frankrig, 07/04/2009. https://doi.org/10.1007/978-3-642-01020-0_16

APA

Voß, T., Hansen, N., & Igel, C. (2009). Recombination for learning strategy parameters in the MO-CMA-ES. I M. Ehrgott, C. M. Fonseca, X. Gandibleux, J-K. Hao, & M. Sevaux (red.), Evolutionary Multi-Criterion Optimization: 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009. Proceedings (s. 155-168). Springer. Lecture notes in computer science, Bind. 5467 https://doi.org/10.1007/978-3-642-01020-0_16

Vancouver

Voß T, Hansen N, Igel C. Recombination for learning strategy parameters in the MO-CMA-ES. I Ehrgott M, Fonseca CM, Gandibleux X, Hao J-K, Sevaux M, red., Evolutionary Multi-Criterion Optimization: 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009. Proceedings. Springer. 2009. s. 155-168. (Lecture notes in computer science, Bind 5467). https://doi.org/10.1007/978-3-642-01020-0_16

Author

Voß, Thomas ; Hansen, Nikolaus ; Igel, Christian. / Recombination for learning strategy parameters in the MO-CMA-ES. Evolutionary Multi-Criterion Optimization: 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009. Proceedings. red. / Matthias Ehrgott ; Carlos M. Fonseca ; Xavier Gandibleux ; Jin-Kao Hao ; Marc Sevaux. Springer, 2009. s. 155-168 (Lecture notes in computer science, Bind 5467).

Bibtex

@inproceedings{bc40603435cb44a79564b068e30cadf3,
title = "Recombination for learning strategy parameters in the MO-CMA-ES",
abstract = "The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population of candidate solutions, which are varied by additive, zero-mean Gaussian mutations. Each individual learns its own covariance matrix for the mutation distribution considering only its parent and offspring. However, the optimal mutation distribution of individuals that are close in decision space are likely to be similar if we presume some notion of continuity of the optimization problem. Therefore, we propose a lateral (inter-individual) transfer of information in the MO-CMA-ES considering also successful mutations of neighboring individuals for the covariance matrix adaptation. We evaluate this idea on common bi-criteria objective functions. The preliminary results show that the new adaptation rule significantly improves the performance of the MO-CMA-ES.",
author = "Thomas Vo{\ss} and Nikolaus Hansen and Christian Igel",
year = "2009",
doi = "10.1007/978-3-642-01020-0_16",
language = "English",
isbn = "978-3-642-01019-4",
series = "Lecture notes in computer science",
publisher = "Springer",
pages = "155--168",
editor = "Matthias Ehrgott and Fonseca, {Carlos M.} and Xavier Gandibleux and Jin-Kao Hao and Marc Sevaux",
booktitle = "Evolutionary Multi-Criterion Optimization",
note = "5th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2009 ; Conference date: 07-04-2009 Through 10-04-2009",

}

RIS

TY - GEN

T1 - Recombination for learning strategy parameters in the MO-CMA-ES

AU - Voß, Thomas

AU - Hansen, Nikolaus

AU - Igel, Christian

PY - 2009

Y1 - 2009

N2 - The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population of candidate solutions, which are varied by additive, zero-mean Gaussian mutations. Each individual learns its own covariance matrix for the mutation distribution considering only its parent and offspring. However, the optimal mutation distribution of individuals that are close in decision space are likely to be similar if we presume some notion of continuity of the optimization problem. Therefore, we propose a lateral (inter-individual) transfer of information in the MO-CMA-ES considering also successful mutations of neighboring individuals for the covariance matrix adaptation. We evaluate this idea on common bi-criteria objective functions. The preliminary results show that the new adaptation rule significantly improves the performance of the MO-CMA-ES.

AB - The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population of candidate solutions, which are varied by additive, zero-mean Gaussian mutations. Each individual learns its own covariance matrix for the mutation distribution considering only its parent and offspring. However, the optimal mutation distribution of individuals that are close in decision space are likely to be similar if we presume some notion of continuity of the optimization problem. Therefore, we propose a lateral (inter-individual) transfer of information in the MO-CMA-ES considering also successful mutations of neighboring individuals for the covariance matrix adaptation. We evaluate this idea on common bi-criteria objective functions. The preliminary results show that the new adaptation rule significantly improves the performance of the MO-CMA-ES.

U2 - 10.1007/978-3-642-01020-0_16

DO - 10.1007/978-3-642-01020-0_16

M3 - Article in proceedings

AN - SCOPUS:78650751826

SN - 978-3-642-01019-4

T3 - Lecture notes in computer science

SP - 155

EP - 168

BT - Evolutionary Multi-Criterion Optimization

A2 - Ehrgott, Matthias

A2 - Fonseca, Carlos M.

A2 - Gandibleux, Xavier

A2 - Hao, Jin-Kao

A2 - Sevaux, Marc

PB - Springer

T2 - 5th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2009

Y2 - 7 April 2009 through 10 April 2009

ER -

ID: 168462009