Encyclopedia of Complexity and Systems Science

Living Edition
| Editors: Robert A. Meyers

Immunecomputing

  • Jon Timmis
Living reference work entry
DOI: https://doi.org/10.1007/978-3-642-27737-5_282-3

Definition of the Subject

Immunecomputing, or artificial immune systems (AIS), has recently emerged as a computational intelligence approach that shows great promise. Inspired by the complexity of the immune system, computer scientists and engineers have created systems that in some way mimic or capture certain computationally appealing properties of the immune system, with the aim of building more robust and adaptable solutions. AIS have been defined by de Castro and Timmis ( 2002b) as:

adaptive systems, inspired by theoretical immunology and observed immune functions, principle and models, which are applied to problem solving.

However, in order to build AIS, an interdisciplinary approach is required that employs modeling of immunology (both mathematical and computational) in order to understand the underlying complexity inherent within the immune system. AIS do not rival their natural counterparts; they do not exhibit the same level of complexity or even perform the same function, but...

Keywords

Innate Immune System Negative Selection Clonal Selection Artificial Immune System Shape Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Bibliography

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Books and Reviews

  1. Cohen I, Segal L (2001) Design principles for the immune system and other distributed autonomous systems. SFT. Oxford University Press, New YorkGoogle Scholar
  2. Ishida Y (2004) Immunity-based systems: a design perspective. Springer, New YorkCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Electronics, Department of Computer ScienceUniversity of YorkYorkUK