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&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;{{Evolutionary algorithms}}&lt;br /&gt;
In [[artificial immune systems]], &amp;#039;&amp;#039;&amp;#039;clonal selection algorithms&amp;#039;&amp;#039;&amp;#039; 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.&amp;lt;ref&amp;gt;{{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}}&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Techniques ==&lt;br /&gt;
*&amp;#039;&amp;#039;&amp;#039;CLONALG&amp;#039;&amp;#039;&amp;#039;: The &amp;#039;&amp;#039;&amp;#039;CLON&amp;#039;&amp;#039;&amp;#039;al selection &amp;#039;&amp;#039;&amp;#039;ALG&amp;#039;&amp;#039;&amp;#039;orithm&amp;lt;ref&amp;gt;&lt;br /&gt;
{{cite journal&lt;br /&gt;
 | last = de Castro&lt;br /&gt;
 | first = L. N.&lt;br /&gt;
 |author2=Von Zuben, F. J.&lt;br /&gt;
 | title = Learning and Optimization Using the Clonal Selection Principle&lt;br /&gt;
 | journal = IEEE Transactions on Evolutionary Computation &lt;br /&gt;
 | volume = 6&lt;br /&gt;
 | issue = 3&lt;br /&gt;
 | year = 2002&lt;br /&gt;
 | pages = 239–251&lt;br /&gt;
 | url = ftp://ftp.dca.fee.unicamp.br/pub/docs/vonzuben/lnunes/ieee_tec01.pdf&lt;br /&gt;
 | archive-url = https://web.archive.org/web/20170706014452/ftp://ftp.dca.fee.unicamp.br/pub/docs/vonzuben/lnunes/ieee_tec01.pdf&lt;br /&gt;
 | archive-date = 2017-07-06&lt;br /&gt;
 | url-status = dead&lt;br /&gt;
 | doi=10.1109/tevc.2002.1011539}}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
*&amp;#039;&amp;#039;&amp;#039;AIRS&amp;#039;&amp;#039;&amp;#039;: The Artificial Immune Recognition System&amp;lt;ref&amp;gt;{{cite journal&lt;br /&gt;
 | last = Watkins&lt;br /&gt;
 | first = Andrew&lt;br /&gt;
 | author2 = Timmis, Jon&lt;br /&gt;
 | author3 = Boggess, Lois&lt;br /&gt;
 | title = Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm&lt;br /&gt;
 | journal = Genetic Programming and Evolvable Machines&lt;br /&gt;
 | volume = 5&lt;br /&gt;
 | issue = 3&lt;br /&gt;
 | year = 2004&lt;br /&gt;
 | pages = 291–317&lt;br /&gt;
 | url = http://www.cse.msstate.edu/%7Eandrew/research/publications/airs.pdf&lt;br /&gt;
 | doi = 10.1023/B:GENP.0000030197.83685.94&lt;br /&gt;
 | citeseerx = 10.1.1.58.1410&lt;br /&gt;
 | s2cid = 13661336&lt;br /&gt;
 | access-date = 2008-11-27&lt;br /&gt;
 | archive-url = https://web.archive.org/web/20090108045124/http://www.cse.msstate.edu/%7Eandrew/research/publications/airs.pdf&lt;br /&gt;
 | archive-date = 2009-01-08&lt;br /&gt;
 | url-status = dead&lt;br /&gt;
 }}&amp;lt;/ref&amp;gt;&lt;br /&gt;
*&amp;#039;&amp;#039;&amp;#039;BCA&amp;#039;&amp;#039;&amp;#039;: The B-Cell Algorithm&amp;lt;ref&amp;gt;&lt;br /&gt;
{{cite conference&lt;br /&gt;
  | last = Kelsey&lt;br /&gt;
  | first = Johnny&lt;br /&gt;
  |author2=Timmis, Jon&lt;br /&gt;
  | title = Immune Inspired Somatic Contiguous Hypermutation for Function Optimisation &lt;br /&gt;
  | book-title = Genetic and Evolutionary Computation (GECCO 2003)&lt;br /&gt;
  | year = 2003&lt;br /&gt;
  | pages = 202&lt;br /&gt;
  | doi = 10.1007/3-540-45105-6_26&lt;br /&gt;
 | citeseerx = 10.1.1.422.515&lt;br /&gt;
  }}&lt;br /&gt;
&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== See also ==&lt;br /&gt;
*[[Artificial immune system]]&lt;br /&gt;
*[[Biologically inspired computing]]&lt;br /&gt;
*[[Computational immunology]]&lt;br /&gt;
*[[Computational intelligence]]&lt;br /&gt;
*[[Evolutionary computation]]&lt;br /&gt;
*[[Immunocomputing]]&lt;br /&gt;
*[[Natural computation]]&lt;br /&gt;
*[[Swarm intelligence]]&lt;br /&gt;
&lt;br /&gt;
== Notes ==&lt;br /&gt;
{{reflist}}&lt;br /&gt;
&lt;br /&gt;
== External links ==&lt;br /&gt;
*[http://www.artificial-immune-systems.org/algorithms.shtml#clonal-alg Clonal Selection Pseudo code] on AISWeb&lt;br /&gt;
*[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&lt;br /&gt;
*[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)&lt;br /&gt;
*[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&lt;br /&gt;
*[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&lt;br /&gt;
&lt;br /&gt;
{{Evolutionary computation}}&lt;br /&gt;
[[Category:Genetic algorithms]]&lt;br /&gt;
[[Category:Artificial immune systems]]&lt;/div&gt;</summary>
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