Clonal selection algorithm: Difference between revisions

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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 lymphocytes improve their response to antigens over time called affinity maturation. These algorithms focus on the Darwinian attributes of the theory where selection is inspired by the affinity of 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 and pattern recognition domains, some of which resemble parallel hill climbing and the genetic algorithm without the recombination operator^[1].

^ Brownlee, Jason. "Clonal Selection Algorithm". Clonal Selection Algorithm.
^ de Castro, L. N.; Von Zuben, F. J. (2002). "Learning and Optimization Using the Clonal Selection Principle" (PDF). IEEE Transactions on Evolutionary Computation. 6 (3): 239–251. doi:10.1109/tevc.2002.1011539.
^ Watkins, Andrew; Timmis, Jon; Boggess, Lois (2004). "Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm" (PDF). Genetic Programming and Evolvable Machines. 5 (3): 291–317. CiteSeerX 10.1.1.58.1410. doi:10.1023/B:GENP.0000030197.83685.94. Archived from the original (PDF) on 2009-01-08. Retrieved 2008-11-27.
^ Kelsey, Johnny; Timmis, Jon (2003). "Immune Inspired Somatic Contiguous Hypermutation for Function Optimisation". Genetic and Evolutionary Computation (GECCO 2003). p. 202. {{cite conference}}: Unknown parameter |booktitle= ignored (|book-title= suggested) (help)

Clonal Selection Pseudo code on AISWeb
CLONALG in Matlab developed by Leandro de Castro and Fernando Von Zuben
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)
AIRS in C++^{[permanent dead link]} developed by Andrew Watkins
BCA in C++^{[permanent dead link]} developed by Johnny Kelsey

@@ Line 17: / Line 17: @@
  | doi=10.1109/tevc.2002.1011539}}
 </ref>
-*'''AIRS''': The Artificial Immune Recognition System<ref>
+*'''AIRS''': The Artificial Immune Recognition System<ref>{{cite journal
-{{cite journal
  | 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
  | journal = Genetic Programming and Evolvable Machines
@@ Line 28: / Line 29: @@
  | pages = 291–317
  | 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>
 {{cite conference