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(Last Modified: 21st October 2013)

New to Artificial Immune Systems?



Or maybe you want to find out just a little bit more about what AIS are and where they came from? On this page, we provide a basic outline of AIS and a brief history (as good as we can tell it). We also provide a list of review papers in AIS that a beginner might find a useful starting point, and a list of active research projects from around the world (please email us if you want your project added).




What are Artificial Immune Systems?


Artificial Immune Systems (AIS) is a diverse area of research that attempts to bridge the divide between immunology and engineering and are developed through the application of techniques such as mathematical and computational modeling of immunology, abstraction from those models into algorithm (and system) design and implementation in the context of engineering. AIS has become known as an area of computer science and engineering that uses immune system metaphors for the creation of novel solutions to problems. Whilst this forms the majority view, AIS is now much wider and is not confined to the development of new algorithms. In a recent paper, immunologist Irun Cohen defines three types of AIS scientists. The first are those of the literal school that build systems in silico to try and do what the actual immune system does (e.g. build computer security systems that discriminate between self and non-self); those of the metaphorical school that look for inspiration from the immune system and build computational systems with the immune system in mind (so the application may be far from analogous to what the immune system does) and a third school of people who aim to understand immunity through the development of computer and mathematical models. AIS is moving into an area of true interdisciplinarity and one of genuine interaction between immunology, mathematics and engineering.


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A Brief History of Artificial Immune Systems



The origins of AIS has its roots in the early theoretical immunology work of J. Doyne Farmer, Alan Perelson and Francisco Varela, with a key work being by Farmer, Packard and Perelson [1]. These works investigated a number of theoretical immune network models proposed to describe the maintenance of immune memory. Whilst controversial from an immunological perspective, these models began to give rise to an interest from the computing community. The most influential people at crossing the divide between computing and immunology in the early days were Hugues Bersini and Stephanie Forrest. It is fair to say that some of the early work by Bersini was very well rooted in immunology, and this is also true of the early work by Forrest. It was these works that formed the basis of a solid foundation for the area of AIS. In the case of Bersini, he concentrated on the immune network theory, examining how the immune system maintained its memory and how one might build models and algorithms mimicing that property. With regards to Forrest, her work was focussed on computer security (in particular network intrusion detection) paying ttention to the abilty of the immune systems to discriminate between self and non-self. These works formed the basis of a great deal of further research by the community on the application of immune inspired techniques to computer security.


Due to a growing amount of work conducted on AIS, the International Conference on Artificial Immune Systems (ICARIS) conference series was started in 2002 and continues to operate. This is the best source of reference material to read in order to grasp the variety of application areas of AIS, and also the developments in algorithms and the more theoretical side of AIS.

[1] Farmer, J. D., N. H. Packard and A. Perelson. "The Immune System, Adaptation, and Machine Learning." Physica D 22(1-3) (1986): 187-204.

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Review Papers in AIS


Most recent first.


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Exisiting AIS Related Projects



Follow these links to the latest AIS related projects (please email Jon Timmis (email address on the home page of AISWeb) if you want your project added):



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