Clonal selection algorithm

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].

Part of a series on the
Evolutionary algorithm
Genetic algorithm
Genetic programming

Techniques
  • CLONALG: The CLONal selection ALGorithm[2]
  • AIRS: The Artificial Immune Recognition System[3]
  • BCA: The B-Cell Algorithm[4]
gollark: > I want to avoid losing this game, is that not fair?No. This is unfair. All shall submit to gibson's rule.
gollark: Down? Why?
gollark: ...
gollark: As of now, *no* reassignments could actually do it.
gollark: We have two days, I'm sure we can make negotiations for reassignments later.

See also

Notes
  1. Brownlee, Jason. "Clonal Selection Algorithm". Clonal Selection Algorithm.
  2. 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.
  3. 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.
  4. Kelsey, Johnny; Timmis, Jon (2003). "Immune Inspired Somatic Contiguous Hypermutation for Function Optimisation". Genetic and Evolutionary Computation (GECCO 2003). p. 202.
  • 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++ developed by Andrew Watkins
  • BCA in C++ developed by Johnny Kelsey
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