Exploiting the Plasticity of Primary and Secondary Response Mechanisms in Artificial Immune Systems

Greensmith, Julie; Jackson, Andrew M.; Spendlove, Ian

Abstract

One of the key properties of the human immune system is to detect the presence of pathogens, and as such there are numberous immune algorithm which perform anomaly detection and pattern recognition. An additional facet of the human immune system is that an appropriate effector response is generated upon the detection of a pathogen - a process termed the primary response. Additionally the human immune system has the ability to remember the appropriate response to a particular pathogen - the secondary response. The complex orchestration of both the primary and secondary responses are highly dynamic - described in immunological terms as plastic. In this paper we present an overview of the the exact mechanisms of the generation of a T-helper cell primary response and the mechanisms by which it instructs secondary responses and discuss how this can be computationally useful in artificial immune system development.

Citation

Greensmith, J., Jackson, A. M., & Spendlove, I. (2016, July). Exploiting the Plasticity of Primary and Secondary Response Mechanisms in Artificial Immune Systems. Presented at GECCO '16 Companion 2016 on Genetic and Evolutionary Computation Conference Companion, Denver, Colorado, USA

• Presentation Conference Type: Edited Proceedings
• Conference Name: GECCO '16 Companion 2016 on Genetic and Evolutionary Computation Conference Companion
• Start Date: Jul 20, 2016
• End Date: Jul 24, 2016
• Acceptance Date: May 8, 2016
• Publication Date: Jul 20, 2016
• Deposit Date: Aug 9, 2016
• Publicly Available Date: Aug 9, 2016
• Peer Reviewed: Peer Reviewed
• Pages: 7-8
• Book Title: Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion - GECCO '16 Companion
• ISBN: 9781450343237
• DOI: https://doi.org/10.1145/2908961.2908962
• Keywords: Artificial Immune Systems; Primary and Secondary Response
• Public URL: https://nottingham-repository.worktribe.com/output/800137
• Publisher URL: http://dl.acm.org/citation.cfm?doid=2908961.2908962
• Additional Information: Published in: Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion; pp. 7-8, ACM : New York, ©2016. ISBN: 9781450343237, doi: 10.1145/2908961.2908962
• Contract Date: Aug 9, 2016