Skip to main content

Research Repository

Advanced Search

On Clonal Selection.

McEwan, Chris; Hart, Emma


Chris McEwan


Clonal selection has been a dominant theme in many immune-inspired algorithms applied to machine learning and optimisation. We examine existing clonal selections algorithms for learning from a theoertical and empirical perspective and assert that the widely accepted computational interpretation of clonal selection is compromised both algorithmically andbiologically. We suggest a more capable abstraction of the clonal selection principle grounded in probabilistic estimation and approximation and demonstrate how it addresses some of the shortcomings in existing algorithms. We further show that by recasting black-box optimisation as a learning problem, the same abstraction may be re-employed; thereby taking steps toward unifying the clonal selection principle and distinguishing it from natural selection.


McEwan, C., & Hart, E. (2011). On Clonal Selection. Theoretical Computer Science, 412, 502-516.

Journal Article Type Article
Publication Date 2011-02
Deposit Date Jan 25, 2011
Print ISSN 0304-3975
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 412
Pages 502-516
Keywords Clonal selection; optimisation;machine learning; EM algorithm;
Public URL
Publisher URL