A dynamic adaptive calibration of the CLONALG immune algorithm

María Cristina Riff; Elizabeth Montero

doi:10.1109/ICAIS.2009.38

A dynamic adaptive calibration of the CLONALG immune algorithm

María Cristina Riff, Elizabeth Montero

Engineering School

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

The control of parameters during the execution of bio-inspired algorithms is an open research area. In this paper, we propose a new parameter control strategy for the immune algorithm CLONALG. Our approach is based on reinforcement learning ideas. We focus our attention on controlling the number of clones and the number of selected cells which follow a mutation process for improvement. Their values allow a trade-off between intensification and diversification of the search. Our approach provides an efficient and low cost adaptive technique for parameter control. We use instances of the Travelling Salesman Problem that has been tackled before by using CLONALG. The results obtained are very encouraging.

Original language	English
Title of host publication	Proceedings of the 2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009
Pages	187-193
Number of pages	7
DOIs	https://doi.org/10.1109/ICAIS.2009.38
Publication status	Published - 1 Dec 2009
Event	2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009 - Klagenfurt, Austria Duration: 24 Sept 2009 → 26 Sept 2009

Publication series

Name	Proceedings of the 2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009

Conference

Conference	2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009
Country/Territory	Austria
City	Klagenfurt
Period	24/09/09 → 26/09/09

Keywords

Artificial immune algorithms
Control
Parameter

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Software
Control and Systems Engineering

Access to Document

10.1109/ICAIS.2009.38

Cite this

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title = "A dynamic adaptive calibration of the CLONALG immune algorithm",

abstract = "The control of parameters during the execution of bio-inspired algorithms is an open research area. In this paper, we propose a new parameter control strategy for the immune algorithm CLONALG. Our approach is based on reinforcement learning ideas. We focus our attention on controlling the number of clones and the number of selected cells which follow a mutation process for improvement. Their values allow a trade-off between intensification and diversification of the search. Our approach provides an efficient and low cost adaptive technique for parameter control. We use instances of the Travelling Salesman Problem that has been tackled before by using CLONALG. The results obtained are very encouraging.",

keywords = "Artificial immune algorithms, Control, Parameter",

author = "Riff, {Mar{\'i}a Cristina} and Elizabeth Montero",

year = "2009",

month = dec,

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doi = "10.1109/ICAIS.2009.38",

language = "English",

isbn = "9780769538273",

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pages = "187--193",

booktitle = "Proceedings of the 2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009",

note = "2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009 ; Conference date: 24-09-2009 Through 26-09-2009",

}

Riff, MC & Montero, E 2009, A dynamic adaptive calibration of the CLONALG immune algorithm. in Proceedings of the 2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009., 5329498, Proceedings of the 2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009, pp. 187-193, 2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009, Klagenfurt, Austria, 24/09/09. https://doi.org/10.1109/ICAIS.2009.38

A dynamic adaptive calibration of the CLONALG immune algorithm. / Riff, María Cristina; Montero, Elizabeth.
Proceedings of the 2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009. 2009. p. 187-193 5329498 (Proceedings of the 2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Montero, Elizabeth

PY - 2009/12/1

Y1 - 2009/12/1

N2 - The control of parameters during the execution of bio-inspired algorithms is an open research area. In this paper, we propose a new parameter control strategy for the immune algorithm CLONALG. Our approach is based on reinforcement learning ideas. We focus our attention on controlling the number of clones and the number of selected cells which follow a mutation process for improvement. Their values allow a trade-off between intensification and diversification of the search. Our approach provides an efficient and low cost adaptive technique for parameter control. We use instances of the Travelling Salesman Problem that has been tackled before by using CLONALG. The results obtained are very encouraging.

AB - The control of parameters during the execution of bio-inspired algorithms is an open research area. In this paper, we propose a new parameter control strategy for the immune algorithm CLONALG. Our approach is based on reinforcement learning ideas. We focus our attention on controlling the number of clones and the number of selected cells which follow a mutation process for improvement. Their values allow a trade-off between intensification and diversification of the search. Our approach provides an efficient and low cost adaptive technique for parameter control. We use instances of the Travelling Salesman Problem that has been tackled before by using CLONALG. The results obtained are very encouraging.

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KW - Control

KW - Parameter

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BT - Proceedings of the 2009 International Conference on Adaptive and Intelligent Systems, ICAIS 2009

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Y2 - 24 September 2009 through 26 September 2009

ER -

A dynamic adaptive calibration of the CLONALG immune algorithm

Abstract

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Conference

Keywords

ASJC Scopus subject areas

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