Clonal selection algorithm - Revision history

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	\| url = ftp://ftp.dca.fee.unicamp.br/pub/docs/vonzuben/lnunes/ieee_tec01.pdf		\| url = ftp://ftp.dca.fee.unicamp.br/pub/docs/vonzuben/lnunes/ieee_tec01.pdf
			\| archive-url = https://web.archive.org/web/20170706014452/ftp://ftp.dca.fee.unicamp.br/pub/docs/vonzuben/lnunes/ieee_tec01.pdf
			\| archive-date = 2017-07-06
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	\| doi=10.1109/tevc.2002.1011539}}		\| doi=10.1109/tevc.2002.1011539}}
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	\| pages = 202		\| pages = 202
	\| doi = 10.1007/3-540-45105-6_26		\| doi = 10.1007/3-540-45105-6_26
			\| citeseerx = 10.1.1.422.515
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	*[http://www.artificial-immune-systems.org/code/bca/BCA.tar.gz BCA in C++]{{dead link\|date=August 2017 \|bot=InternetArchiveBot \|fix-attempted=yes }} developed by Johnny Kelsey		*[http://www.artificial-immune-systems.org/code/bca/BCA.tar.gz BCA in C++]{{dead link\|date=August 2017 \|bot=InternetArchiveBot \|fix-attempted=yes }} developed by Johnny Kelsey

			{{Evolutionary computation}}
	[[Category:Genetic algorithms]]		[[Category:Genetic algorithms]]
	[[Category:Artificial immune systems]]		[[Category:Artificial immune systems]]

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	\|author2=Timmis, Jon		\|author2=Timmis, Jon
	\| title = Immune Inspired Somatic Contiguous Hypermutation for Function Optimisation		\| title = Immune Inspired Somatic Contiguous Hypermutation for Function Optimisation
	\| ~~booktitle~~ = Genetic and Evolutionary Computation (GECCO 2003)		\| book-title = Genetic and Evolutionary Computation (GECCO 2003)
	\| year = 2003		\| year = 2003
	\| pages = 202		\| pages = 202

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	{{Evolutionary algorithms}}		{{Evolutionary algorithms}}
	In [[artificial immune systems]], '''clonal selection algorithms''' are a class of algorithms inspired by the [[clonal selection]] theory of [[acquired immunity]] that explains how B and T [[lymphocyte]]s improve their response to [[antigens]] over time called [[affinity maturation]]. These algorithms focus on the [[Universal Darwinism\|Darwinian]] attributes of the theory where selection is inspired by the affinity of [[antigen-antibody interaction\|antigen-antibody interactions]], reproduction is inspired by [[cell division]], and variation is inspired by [[somatic hypermutation]]. Clonal selection algorithms are most commonly applied to [[Optimization (mathematics)\|optimization]] and [[pattern recognition]] domains, some of which resemble parallel [[hill climbing]] and the [[genetic algorithm]] without the recombination operator<ref>{{Cite web\|url=http://www.cleveralgorithms.com/nature-inspired/immune/clonal_selection_algorithm.html\|title=Clonal Selection Algorithm\|last=Brownlee\|first=Jason\|website=Clonal Selection Algorithm}}</ref>.		In [[artificial immune systems]], '''clonal selection algorithms''' are a class of algorithms inspired by the [[clonal selection]] theory of [[acquired immunity]] that explains how B and T [[lymphocyte]]s improve their response to [[antigens]] over time called [[affinity maturation]]. These algorithms focus on the [[Universal Darwinism\|Darwinian]] attributes of the theory where selection is inspired by the affinity of [[antigen-antibody interaction\|antigen-antibody interactions]], reproduction is inspired by [[cell division]], and variation is inspired by [[somatic hypermutation]]. Clonal selection algorithms are most commonly applied to [[Optimization (mathematics)\|optimization]] and [[pattern recognition]] domains, some of which resemble parallel [[hill climbing]] and the [[genetic algorithm]] without the recombination operator.<ref>{{Cite web\|url=http://www.cleveralgorithms.com/nature-inspired/immune/clonal_selection_algorithm.html\|title=Clonal Selection Algorithm\|last=Brownlee\|first=Jason\|website=Clonal Selection Algorithm}}</ref>

	== Techniques ==		== Techniques ==

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	\| doi = 10.1023/B:GENP.0000030197.83685.94		\| doi = 10.1023/B:GENP.0000030197.83685.94
	\| citeseerx = 10.1.1.58.1410		\| citeseerx = 10.1.1.58.1410
			\| s2cid = 13661336
	\| access-date = 2008-11-27		\| access-date = 2008-11-27
	\| archive-url = https://web.archive.org/web/20090108045124/http://www.cse.msstate.edu/%7Eandrew/research/publications/airs.pdf		\| archive-url = https://web.archive.org/web/20090108045124/http://www.cse.msstate.edu/%7Eandrew/research/publications/airs.pdf
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	\| year = 2003		\| year = 2003
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	\| ~~url~~ = ~~https://doi.org/~~10.1007~~%2F3~~-540-45105-6_26 }}		\| doi = 10.1007/3-540-45105-6_26
			}}
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	*[http://www.artificial-immune-systems.org/algorithms.shtml#clonal-alg Clonal Selection Pseudo code] on AISWeb		*[http://www.artificial-immune-systems.org/algorithms.shtml#clonal-alg Clonal Selection Pseudo code] on AISWeb
	*[https://web.archive.org/web/20090711163953/http://www.dca.fee.unicamp.br/~lnunes/manual.html CLONALG in Matlab] developed by Leandro de Castro and Fernando Von Zuben		*[https://web.archive.org/web/20090711163953/http://www.dca.fee.unicamp.br/~lnunes/manual.html CLONALG in Matlab] developed by Leandro de Castro and Fernando Von Zuben
	*[http://optalgtoolkit.sourceforge.net Optimization Algorithm Toolkit] in Java developed by Jason Brownlee which includes the following clonal selection algorithms: Adaptive Clonal Selection (ACS), Optimization Immune Algorithm (opt-IMMALG), Optimization Immune Algorithm (opt-IA), Clonal Selection Algorithm (CLONALG, CLONALG1, CLONALG2), B-Cell Algorithm (BCA), Cloning, Information Gain, Aging (CLIGA), Immunological Algorithm (IA)		*[https://web.archive.org/web/20081224175602/http://optalgtoolkit.sourceforge.net/ Optimization Algorithm Toolkit] in Java developed by Jason Brownlee which includes the following clonal selection algorithms: Adaptive Clonal Selection (ACS), Optimization Immune Algorithm (opt-IMMALG), Optimization Immune Algorithm (opt-IA), Clonal Selection Algorithm (CLONALG, CLONALG1, CLONALG2), B-Cell Algorithm (BCA), Cloning, Information Gain, Aging (CLIGA), Immunological Algorithm (IA)
	*[http://www.artificial-immune-systems.org/code/airs/airs_andrew.tar.gz AIRS in C++]{{dead link\|date=August 2017 \|bot=InternetArchiveBot \|fix-attempted=yes }} developed by Andrew Watkins		*[http://www.artificial-immune-systems.org/code/airs/airs_andrew.tar.gz AIRS in C++]{{dead link\|date=August 2017 \|bot=InternetArchiveBot \|fix-attempted=yes }} developed by Andrew Watkins
	*[http://www.artificial-immune-systems.org/code/bca/BCA.tar.gz BCA in C++]{{dead link\|date=August 2017 \|bot=InternetArchiveBot \|fix-attempted=yes }} developed by Johnny Kelsey		*[http://www.artificial-immune-systems.org/code/bca/BCA.tar.gz BCA in C++]{{dead link\|date=August 2017 \|bot=InternetArchiveBot \|fix-attempted=yes }} developed by Johnny Kelsey

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	\| year = 2003		\| year = 2003
	\| pages = 202		\| pages = 202
	\| url = ~~http~~://~~www~~.~~springerlink~~.~~com/content/jmdkyhnrthmec78v/~~ }}		\| url = https://doi.org/10.1007%2F3-540-45105-6_26 }}
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	\| doi=10.1109/tevc.2002.1011539}}		\| doi=10.1109/tevc.2002.1011539}}
	</ref>		</ref>
	*'''AIRS''': The Artificial Immune Recognition System<ref>		*'''AIRS''': The Artificial Immune Recognition System<ref>{{cite journal
	{{cite journal
	\| last = Watkins		\| last = Watkins
	\| first = Andrew \|author2=Timmis, Jon \|author3=Boggess, Lois		\| first = Andrew
			\| author2 = Timmis, Jon
			\| author3 = Boggess, Lois
	\| title = Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm		\| title = Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm
	\| journal = Genetic Programming and Evolvable Machines		\| journal = Genetic Programming and Evolvable Machines
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	\| pages = 291–317		\| pages = 291–317
	\| url = http://www.cse.msstate.edu/%7Eandrew/research/publications/airs.pdf		\| url = http://www.cse.msstate.edu/%7Eandrew/research/publications/airs.pdf
	\| doi = 10.1023/B:GENP.0000030197.83685.94 \| citeseerx = 10.1.1.58.1410 }}		\| doi = 10.1023/B:GENP.0000030197.83685.94
			\| citeseerx = 10.1.1.58.1410
			\| access-date = 2008-11-27
⚫	</ref>
			\| archive-url = https://web.archive.org/web/20090108045124/http://www.cse.msstate.edu/%7Eandrew/research/publications/airs.pdf
			\| archive-date = 2009-01-08
			\| url-status = dead
		⚫	}}</ref>
	*'''BCA''': The B-Cell Algorithm<ref>		*'''BCA''': The B-Cell Algorithm<ref>
	{{cite conference		{{cite conference

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← Previous revision		Revision as of 15:25, 14 October 2019
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	{{Evolutionary algorithms}}		{{Evolutionary algorithms}}
	In [[artificial immune systems]], '''clonal selection algorithms''' are a class of algorithms inspired by the [[clonal selection]] theory of [[acquired immunity]] that explains how B and T [[lymphocyte]]s improve their response to [[antigens]] over time called [[affinity maturation]]. These algorithms focus on the [[Universal Darwinism\|Darwinian]] attributes of the theory where selection is inspired by the affinity of [[antigen-antibody interaction\|antigen-antibody interactions]], reproduction is inspired by [[cell division]], and variation is inspired by [[somatic hypermutation]]. Clonal selection algorithms are most commonly applied to [[Optimization (mathematics)\|optimization]] and [[pattern recognition]] domains, some of which resemble parallel [[hill climbing]] and the [[genetic algorithm]] without the recombination operator<ref>{{Cite web\|url=http://www.cleveralgorithms.com/nature-inspired/immune/clonal_selection_algorithm.html\|title=Clonal Selection Algorithm\|last=Brownlee\|first=Jason~~\|date=~~\|website=Clonal Selection Algorithm~~\|archive-url=\|archive-date=\|dead-url=\|access-date=~~}}</ref>.		In [[artificial immune systems]], '''clonal selection algorithms''' are a class of algorithms inspired by the [[clonal selection]] theory of [[acquired immunity]] that explains how B and T [[lymphocyte]]s improve their response to [[antigens]] over time called [[affinity maturation]]. These algorithms focus on the [[Universal Darwinism\|Darwinian]] attributes of the theory where selection is inspired by the affinity of [[antigen-antibody interaction\|antigen-antibody interactions]], reproduction is inspired by [[cell division]], and variation is inspired by [[somatic hypermutation]]. Clonal selection algorithms are most commonly applied to [[Optimization (mathematics)\|optimization]] and [[pattern recognition]] domains, some of which resemble parallel [[hill climbing]] and the [[genetic algorithm]] without the recombination operator<ref>{{Cite web\|url=http://www.cleveralgorithms.com/nature-inspired/immune/clonal_selection_algorithm.html\|title=Clonal Selection Algorithm\|last=Brownlee\|first=Jason\|website=Clonal Selection Algorithm}}</ref>.

	== Techniques ==		== Techniques ==