Search Swinburne Research Bank
Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/25529
 Download PDF (13 pages) (Adobe Acrobat PDF, -1 bytes) |
- Title
- Clonal selection algorithms
- Author(s)
- Brownlee, Jason
- Abstract
- Inspired by Darwin’s theory of natural selection to explain the diversity and adaptability of life, Burnet’s clonal selection theory explains the diversity and learning properties of the acquired immune system of vertebrates. In a similar mirroring manner to the field of evolutionary computation that attempts to use the principles of the Darwinian theory and genetics to address practical engineering problems a new field of study called ‘Clonal Selection Algorithms’ has emerged that attempts the same task by abstracting and applying the principles of Burnet’s foundational immunological theory. This paper provides a summary of this new field of clonal selection algorithms and proposes an algorithm taxonomy a standardized nomenclature and a general model of such algorithms. Finally the field is compared and contrasted to the field of evolutionary computation and general research trends are discussed.
- Publication type
- Technical report
- Research centre
- Swinburne University of Technology. Faculty of Information and Communication Technologies. Centre for Information Technology Research
- Source
- Complex Intelligent Systems : technical reports
- Publication year
- 2007
- Keyword(s)
- AIS; Algorithm review; Artificial immune systems; Clonal selection algorithm; Clonal selection principle; Clonal selection theory; CSA
- Publisher
- Swinburne University of Technology
- Publisher URL
- http://www.ict.swin.edu.au/personal/jbrownlee/#2007
- Copyright
- Copyright © 2007 Jason Brownlee.
- Full text
