Boosting the Immune System
Much of contemporary research in Artificial Immune Systems (AIS) has partitioned into either algorithmic machine learning and optimisation, or modelling biologically plausible dynamical systems, with little overlap between. Although the balance is latterly beginning to be redressed (e.g. ), we propose that this dichotomy is somewhat to blame for the lack of significant advancement of the field in either direction. This paper outlines how an inappropriate interpretation of Perelson’s shape-space formalism has largely contributed to this dichotomy, as it neither scales to machine-learning requirements nor makes any operational distinction between signals and context.
We illustrate these issues and attempt to derive both a more biologically plausible and statistically solid foundation for an online, unsupervised artificial immune system. By extending a mathematical model of immunological tolerance, and grounding it in contemporary machine learning, we minimise any recourse to “reasoning by metaphor” and demonstrate one view of how both research agendas might still complement each other.
KeywordsImmunological Tolerance Immune Network Clonal Selection Algorithm Peripheral Immune System Immune Repertoire
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- 1.Aggarwal, C.C., Hinneburg, A., Keim, D.A.: On the surprising behavior of distance metrics in high dimensional space. In: Van den Bussche, J., Vianu, V. (eds.) ICDT 2001. LNCS, vol. 1973. Springer, Heidelberg (2000)Google Scholar
- 6.Cohen, I.R., Segel, L.A.: Design Principles for the Immune System and Other Distributed Autonomous Systems. Oxford University Press, Oxford (2001)Google Scholar
- 7.Ferrer, R., Cancho, I., Sole, R.: The small-world of human language. In: Proceedings of the Royal Society of London (2001)Google Scholar
- 11.Janeway, C.A., Travers, P., Walport, M., Schlomchik, M.: Immunobiology, Garland (2001)Google Scholar
- 12.Jerne, N.K.: The generative grammer of the immune system. Nobel Lecture (1984)Google Scholar
- 14.McEwan, C., Hart, E., Paechter, B.: Towards a model of immunological tolerance and autonomous learning. Natural Computing (submitted, 2008)Google Scholar
- 16.Stewart, J., Carneiro, J.: Artificial Immune Systems and their Applications. In: The central and the peripheral immune system: What is the relationship?, pp. 47–64. Springer, Heidelberg (1998)Google Scholar
- 17.Stibor, T., Timmis, J., Eckert, C.: On the use of hyperspheres in artificial immune systems as antibody recognition regions. In: Bersini, H., Carneiro, J. (eds.) ICARIS 2006. LNCS, vol. 4163. Springer, Heidelberg (2006)Google Scholar
- 19.Varela, F.J., Coutinho, A.: Second generation immune networks. Immunology Today 12(5), 159–166 (1991)Google Scholar