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Clonal selection algorithm

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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.

Techniques

  • CLONALG: The CLONal selection ALGorithm [1].
  • AIRS: The Artificial Immune Recognition System [2].
  • BCA: The B-Cell Algorithm [3].

See also

Notes

  1. ^ de Castro, L. N. (2002). "Learning and Optimization Using the Clonal Selection Principle" (PDF). IEEE Transactions on Evolutionary Computation, Special Issue on Artificial Immune Systems. 6 (3). IEEE: 239–251. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)
  2. ^ Watkins, Andrew (2004). "Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm" (PDF). Genetic Programming and Evolvable Machines. 5 (3): 291–317. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)
  3. ^ Kelsey, Johnny (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); Unknown parameter |coauthors= ignored (|author= suggested) (help)

References

  • Jason Brownlee. Clonal Selection Algorithms, Technical Report. Victoria, Australia: Complex Intelligent Systems Laboratory (CIS), Centre for Information Technology Research (CITR), Faculty of Information and Communication Technologies (ICT), Swinburne University of Technology; 2007 Feb; Technical Report ID: 070209A.
  • 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
  • AIRS in Java developed by Jason Brownlee as a plug-in for WEKA
  • BCA in C++ developed by Johnny Kelsey
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