Uwe Aickelin
Artificial Immune Systems
Aickelin, Uwe; Dasgupta, Dipankar; Gu, Feng
Authors
Dipankar Dasgupta
Feng Gu
Contributors
Edmund Burke
Editor
GRAHAM KENDALL GRAHAM.KENDALL@NOTTINGHAM.AC.UK
Editor
Abstract
The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self or nonself substances. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years.
Citation
Aickelin, U., Dasgupta, D., & Gu, F. (2014). Artificial Immune Systems. In E. Burke, & G. Kendall (Eds.), Search methodologies: introductory tutorials in optimization and decision support techniques. 2nd edition (187-211). Springer. https://doi.org/10.1007/978-1-4614-6940-7_7
Online Publication Date | Jul 9, 2013 |
---|---|
Publication Date | 2014 |
Deposit Date | Sep 27, 2014 |
Publicly Available Date | Mar 29, 2024 |
Peer Reviewed | Peer Reviewed |
Pages | 187-211 |
Book Title | Search methodologies: introductory tutorials in optimization and decision support techniques. 2nd edition |
ISBN | 9781461469391 |
DOI | https://doi.org/10.1007/978-1-4614-6940-7_7 |
Keywords | Artificial, Immune, Systems |
Public URL | https://nottingham-repository.worktribe.com/output/997848 |
Publisher URL | http://link.springer.com/chapter/10.1007/978-1-4614-6940-7_7 |
Additional Information | The final publication is available at Springer via http://dx.doi.org/10.1007/978-1-4614-6940-7_7 |
Files
aickelin2014.pdf
(363 Kb)
PDF
You might also like
A Method for Evaluating Options for Motif Detection in Electricity Meter Data
(2018)
Journal Article
Using simulation to incorporate dynamic criteria into multiple criteria decision making
(2017)
Journal Article
THCluster: herb supplements categorization for precision traditional Chinese medicine
(2017)
Conference Proceeding
Measuring behavioural change of players in public goods game
(2017)
Book Chapter
Robust datamining
(2017)
Conference Proceeding
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: digital-library-support@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search