A Markov chain model of the B-cell algorithm

Edward Clark; Andrew Hone; Jon Timmis

doi:10.1007/11536444_24

A Markov chain model of the B-cell algorithm

Edward Clark^*, Andrew Hone, Jon Timmis

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (Non-Journal item)

35 Citations (Scopus)

Abstract

An exact Markov chain model of the B-cell algorithm (BCA) is constructed via a novel possible transit method. The model is used to formulate a proof that the BCA is convergent absolute under a very broad set of conditions. Results from a simple numerical example are presented, we use this to demonstrate how the model can be applied to increase understanding of the performance of the BCA in optimizing function landscapes as well as giving insight into the optimal parameter settings for the BCA.

Original language	English
Title of host publication	Artificial Immune Systems
Subtitle of host publication	4th International Conference, ICARIS 2005, Banff, Alberta, Canada, August 14-17, 2005, Proceedings
Publisher	Springer Nature
Pages	318-330
Number of pages	13
Volume	3627
DOIs	https://doi.org/10.1007/11536444_24
Publication status	Published - 2005
Event	4th International Conference on Artificial Immune Systems, ICARIS 2005 - Banff, Alta., Canada Duration: 14 Aug 2005 → 17 Aug 2005

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Nature
ISSN (Print)	0302-9743

Conference

Conference	4th International Conference on Artificial Immune Systems, ICARIS 2005
Country/Territory	Canada
City	Banff, Alta.
Period	14 Aug 2005 → 17 Aug 2005

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10.1007/11536444_24

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title = "A Markov chain model of the B-cell algorithm",

abstract = "An exact Markov chain model of the B-cell algorithm (BCA) is constructed via a novel possible transit method. The model is used to formulate a proof that the BCA is convergent absolute under a very broad set of conditions. Results from a simple numerical example are presented, we use this to demonstrate how the model can be applied to increase understanding of the performance of the BCA in optimizing function landscapes as well as giving insight into the optimal parameter settings for the BCA.",

author = "Edward Clark and Andrew Hone and Jon Timmis",

year = "2005",

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volume = "3627",

series = "Lecture Notes in Computer Science",

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booktitle = "Artificial Immune Systems",

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Clark, E, Hone, A & Timmis, J 2005, A Markov chain model of the B-cell algorithm. in Artificial Immune Systems: 4th International Conference, ICARIS 2005, Banff, Alberta, Canada, August 14-17, 2005, Proceedings. vol. 3627, Lecture Notes in Computer Science, Springer Nature, pp. 318-330, 4th International Conference on Artificial Immune Systems, ICARIS 2005, Banff, Alta., Canada, 14 Aug 2005. https://doi.org/10.1007/11536444_24

A Markov chain model of the B-cell algorithm. / Clark, Edward; Hone, Andrew; Timmis, Jon.
Artificial Immune Systems: 4th International Conference, ICARIS 2005, Banff, Alberta, Canada, August 14-17, 2005, Proceedings. Vol. 3627 Springer Nature, 2005. p. 318-330 (Lecture Notes in Computer Science).

Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (Non-Journal item)

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A Markov chain model of the B-cell algorithm

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