Artificial Immune System (IMS) is a class of automated computing systems that are based on the principles and processes of the vertebrate immune system. Typically, such algorithms use the memory and learning ability of the immune system to solve problems.
Content
Definition
Artificial immune system (IMS) is an adaptive computing system that uses the models, principles, mechanisms and functions described in theoretical immunology that are used to solve applied problems [1] .
Despite the fact that natural immune systems have not been fully studied, today there are at least three theories that explain the functioning of the immune system and describe the interaction of its elements, namely, the theory of negative selection, the theory of clonal selection and the theory of the immune network. They formed the basis for the creation of three algorithms for the functioning of IMS.
History
IIS appeared in the mid-1980s in articles by Farmer, Packard, and Perelson (Farmer, Packard, Perelson) (1986) and Bersini and Varela (Bersini, Varela) (1990) on immune networks. However, the basics of IMS were established only by the mid-1990s. Forrest (negative selection) and Kephart [2] published their first article on IMS in 1994 and Dasgupta conducted extensive research on the negative selection algorithm. Hunt and Cook (Hunt, Cooke) began work on the immune network algorithm in 1995; Timmis and Neal continued this work and made some improvements. The first book on artificial immune systems was edited by Dasgupta in 1999.
Methods
General methods are based on specific immunological theories that explain the functions and behavior of the mammalian adaptive immune system.
- The clonal selection algorithm is a class of algorithms based on the theory of clone selection of acquired immunity, which explains how B and T lymphocytes improve their response to antigens over time, which is called affinity maturation. These algorithms focus on attributes of Darwin's theory, where the choice is based on the proximity of the interaction of antigens and antibodies and reproduction on the principle of cell division and variations based on somatic hypermutations.
- Negative selection algorithm
- Immune Network Algorithm
- Dendritic algorithm
Notes
- ↑ de Castro, Leandro N. Artificial Immune Systems: A New Computational Intelligence Approach . - Springer , 2002. - P. 57-58. - ISBN 1852335947 , 9781852335946.
- ↑ Kephart, JO (1994). "A biologically inspired immune system for computers." Proceedings of Artificial Life IV: The Fourth International Workshop on the Synthesis and Simulation of Living Systems : 130–139, MIT Press.