Clonal selection algorithm

Evolutionary 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.^[1]

Techniques

^ 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. S2CID 13661336. 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. CiteSeerX 10.1.1.422.515. doi:10.1007/3-540-45105-6_26.

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

v t e Evolutionary computation
Main Topics	Convergence (evolutionary computing) Evolutionary algorithm Evolutionary data mining Evolutionary multimodal optimization Human-based evolutionary computation Interactive evolutionary computation
Algorithms	Cellular evolutionary algorithm Covariance Matrix Adaptation Evolution Strategy (CMA-ES) Cultural algorithm Differential evolution Evolutionary programming Genetic algorithm Genetic programming Gene expression programming Evolution strategy Natural evolution strategy Neuroevolution Learning classifier system
Related techniques	Swarm intelligence Ant colony optimization Bees algorithm Cuckoo search Particle swarm optimization Bacterial Colony Optimization
Metaheuristic methods	Firefly algorithm Harmony search Gaussian adaptation Memetic algorithm
Related topics	Artificial development Artificial intelligence Artificial life Digital organism Evolutionary robotics Fitness function Fitness landscape Fitness approximation Genetic operators Interactive evolutionary computation No free lunch in search and optimization Machine learning Mating pool Program synthesis
Journals	Evolutionary Computation (journal)

This page was last edited on 11 January 2024, at 23:11