Adaptive Selection of Helper-Objectives with Reinforcement Learning

Arina Buzdalova; Maxim Buzdalov

doi:10.1109/ICMLA.2012.159

Adaptive Selection of Helper-Objectives with Reinforcement Learning

ITMO University

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Trafodion Cynhadledd (ISBN)

8 Dyfyniadau (Scopus)

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In this paper a previously proposed method of choosing auxiliary fitness functions is applied to adaptive selection of helper-objectives. Helper-objectives are used in evolutionary computation to enhance the optimization of the primary objective. The method based on choosing between objectives of a single-objective evolutionary algorithm with reinforcement learning is briefly described. It is tested on a model problem. From the results of the experiment, it can be concluded that the method allows to automatically select the most effective helper-objectives and ignore the ineffective ones. It is also shown that the proposed method outperforms multi-objective evolutionary algorithms, that were used with helper-objectives originally.

Iaith wreiddiol	Saesneg
Teitl	ICMLA '12
Is-deitl	Proceedings of the 2012 11th International Conference on Machine Learning and Applications
Cyhoeddwr	Institute of Electrical and Electronics Engineers
Tudalennau	66-67
Nifer y tudalennau	2
Cyfrol	2
ISBN (Argraffiad)	978-1-4673-4651-1
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1109/ICMLA.2012.159
Statws	Cyhoeddwyd - 12 Rhag 2012
Cyhoeddwyd yn allanol	Ie
Digwyddiad	11th IEEE International Conference on Machine Learning and Applications - Cancan, Mecsico Hyd: 12 Rhag 2012 → 15 Rhag 2012

Cynhadledd

Cynhadledd	11th IEEE International Conference on Machine Learning and Applications
Teitl cryno	ICMLA 2012
Gwlad/Tiriogaeth	Mecsico
Dinas	Cancan
Cyfnod	12 Rhag 2012 → 15 Rhag 2012

Mynediad at Ddogfen

10.1109/ICMLA.2012.159

Cysylltiad parhaol

Dolen barhaus

Ffeiliau eraill a chysylltiadau

https://www.scopus.com/pages/publications/84873590563

Dyfynnu hyn

@inproceedings{d8a8ab4abab3403c8e66cf00e7904871,

title = "Adaptive Selection of Helper-Objectives with Reinforcement Learning",

abstract = "In this paper a previously proposed method of choosing auxiliary fitness functions is applied to adaptive selection of helper-objectives. Helper-objectives are used in evolutionary computation to enhance the optimization of the primary objective. The method based on choosing between objectives of a single-objective evolutionary algorithm with reinforcement learning is briefly described. It is tested on a model problem. From the results of the experiment, it can be concluded that the method allows to automatically select the most effective helper-objectives and ignore the ineffective ones. It is also shown that the proposed method outperforms multi-objective evolutionary algorithms, that were used with helper-objectives originally. ",

author = "Arina Buzdalova and Maxim Buzdalov",

year = "2012",

month = dec,

day = "12",

doi = "10.1109/ICMLA.2012.159",

language = "English",

isbn = "978-1-4673-4651-1",

volume = "2",

pages = "66--67",

booktitle = "ICMLA '12",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "11th IEEE International Conference on Machine Learning and Applications, ICMLA 2012 ; Conference date: 12-12-2012 Through 15-12-2012",

}

Buzdalova, A & Buzdalov, M 2012, Adaptive Selection of Helper-Objectives with Reinforcement Learning. yn ICMLA '12: Proceedings of the 2012 11th International Conference on Machine Learning and Applications. cyfrol. 2, Institute of Electrical and Electronics Engineers, tt. 66-67, 11th IEEE International Conference on Machine Learning and Applications, Cancan, Mecsico, 12 Rhag 2012. https://doi.org/10.1109/ICMLA.2012.159

Adaptive Selection of Helper-Objectives with Reinforcement Learning. / Buzdalova, Arina ; Buzdalov, Maxim.
ICMLA '12: Proceedings of the 2012 11th International Conference on Machine Learning and Applications. Cyfrol 2 Institute of Electrical and Electronics Engineers, 2012. t. 66-67.

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Trafodion Cynhadledd (ISBN)

TY - GEN

T1 - Adaptive Selection of Helper-Objectives with Reinforcement Learning

AU - Buzdalova, Arina

AU - Buzdalov, Maxim

PY - 2012/12/12

Y1 - 2012/12/12

N2 - In this paper a previously proposed method of choosing auxiliary fitness functions is applied to adaptive selection of helper-objectives. Helper-objectives are used in evolutionary computation to enhance the optimization of the primary objective. The method based on choosing between objectives of a single-objective evolutionary algorithm with reinforcement learning is briefly described. It is tested on a model problem. From the results of the experiment, it can be concluded that the method allows to automatically select the most effective helper-objectives and ignore the ineffective ones. It is also shown that the proposed method outperforms multi-objective evolutionary algorithms, that were used with helper-objectives originally.

AB - In this paper a previously proposed method of choosing auxiliary fitness functions is applied to adaptive selection of helper-objectives. Helper-objectives are used in evolutionary computation to enhance the optimization of the primary objective. The method based on choosing between objectives of a single-objective evolutionary algorithm with reinforcement learning is briefly described. It is tested on a model problem. From the results of the experiment, it can be concluded that the method allows to automatically select the most effective helper-objectives and ignore the ineffective ones. It is also shown that the proposed method outperforms multi-objective evolutionary algorithms, that were used with helper-objectives originally.

UR - https://www.scopus.com/pages/publications/84873590563

U2 - 10.1109/ICMLA.2012.159

DO - 10.1109/ICMLA.2012.159

M3 - Conference Proceeding (ISBN)

SN - 978-1-4673-4651-1

VL - 2

SP - 66

EP - 67

BT - ICMLA '12

PB - Institute of Electrical and Electronics Engineers

T2 - 11th IEEE International Conference on Machine Learning and Applications

Y2 - 12 December 2012 through 15 December 2012

ER -

Adaptive Selection of Helper-Objectives with Reinforcement Learning

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