Modelling danger and anergy in artificial immune systems

Steve Cayzer, Julie Sullivan

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

4 Citations (SciVal)


Artificial Immune Systems are engineering systems which have been inspired from the functioning of the biological immune system. We present an immune system model which incorporates two biologically motivated mechanisms to protect against autoimmune reactions, or false positives. The first, anergy, has been subject to the intense focus of immunologists as a possible key to autoimmune disease. The second is danger theory, which has attracted much interest as a possible alternative to traditional self-nonself selection models.We adopt a published immunological model, validate and extend it. Using the same calculations and assumptions as the original model, we integrate danger theory into the software.Without anergy, both models - the original and the danger model - produce similar results. When anergy is added, both models' performance improves. However, there seems to be some synergy between the mechanisms; anergy has a greater effect on the danger model than the original model. These findings should be of interest both to AIS practitioners and to the immunological community.

Original languageEnglish
Title of host publicationProceedings of GECCO 2007: Genetic and Evolutionary Computation Conference
Number of pages7
Publication statusPublished - 2007
Event9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007 - London, UK United Kingdom
Duration: 7 Jul 200711 Jul 2007


Conference9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007
Country/TerritoryUK United Kingdom


  • AIS
  • Anergy
  • Danger
  • Danger theory
  • Immune
  • Modelling


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