Skip to main content

Part of the book series: Studies in Computational Intelligence ((SCI,volume 249))

  • 806 Accesses

Artificial Immune Systems

The Artificial Immune System paradigm (AIS) is inspired by the biological immune system whose main goal is to protect the human body from the attack of foreign pathogens such as virus, fungus or other parasites. The biological immune system is capable of distinguishing between the normal components of our organism and the foreign materials that can cause us harm that are known as antigens. The molecules called antibodies play the main role in the immune system response in that the immune response is specific to a certain antigen. Thus when an antigen is detected, those antibodies that best recognize an antigen will proliferate by cloning. Then the new cloned cells undergo a mutation or hypermutation process so that their receptor population will be increased. These mutations experienced by the clones are inversely proportional to their affinity to the antigen, which means that those antibodies with the highest affinity suffer the lowest mutation rates, whereas the lowest affinity antibodies have high mutation rates. After this mutation process ends, the antibodies’ affinity in the immune system is improved and the immune system returns to its normal condition by eliminating the extra cells. However, some cells are turned into memory cells so that when the immune system is later attacked by the same type of antigen (or a similar one), these memory cells are activated, presenting a better and more efficient response. Artificial immune systems are motivated from such immunology in order to develop systems capable of performing a wide range of tasks.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Barbakh, W.A., Wu, Y., Fyfe, C. (2009). Artificial Immune Systems. In: Non-Standard Parameter Adaptation for Exploratory Data Analysis. Studies in Computational Intelligence, vol 249. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04005-4_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04005-4_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04004-7

  • Online ISBN: 978-3-642-04005-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics