Topic
Immune network theory
About: Immune network theory is a research topic. Over the lifetime, 99 publications have been published within this topic receiving 11987 citations.
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Journal Article•
2,999 citations
TL;DR: This paper proposes a computational implementation of the clonal selection principle that explicitly takes into account the affinity maturation of the immune response and derives two versions of the algorithm, derived primarily to perform machine learning and pattern recognition tasks.
Abstract: The clonal selection principle is used to explain the basic features of an adaptive immune response to an antigenic stimulus. It establishes the idea that only those cells that recognize the antigens (Ag's) are selected to proliferate. The selected cells are subject to an affinity maturation process, which improves their affinity to the selective Ag's. This paper proposes a computational implementation of the clonal selection principle that explicitly takes into account the affinity maturation of the immune response. The general algorithm, named CLONALG, is derived primarily to perform machine learning and pattern recognition tasks, and then it is adapted to solve optimization problems, emphasizing multimodal and combinatorial optimization. Two versions of the algorithm are derived, their computational cost per iteration is presented, and a sensitivity analysis in relation to the user-defined parameters is given. CLONALG is also contrasted with evolutionary algorithms. Several benchmark problems are considered to evaluate the performance of CLONALG and it is also compared to a niching method for multimodal function optimization.
2,235 citations
Book•
23 Sep 2002
TL;DR: The AIS in Context with Other Computational Intelligence Paradigms and Case Studies shows how the immune system in context with other biological systems and other paradigms has changed since the 1970s.
Abstract: Introduction.- Fundamentals of the Immune System.- A Framework for Engineering Artificial Immune Systems.- A Survey of Artificial Immune Systems.- The Immune System in Context with Other Biological Systems.- AIS in Context with Other Computational Intelligence Paradigms.- Case Studies.- Conclusions and Future Trends.- References.- Appendix I: Glossary of Biological Terms.- Appendix II: Pseudocode for Immune Algorithms.- Appendix III: WEB Resources on Artificial Immune Systems. Index.
1,683 citations
TL;DR: A dynamical model for the immune system is described that is based on the network hypothesis of Jerne, and is simple enough to simulate on a computer, and has a strong similarity to an approach to learning and artificial intelligence introduced by Holland, called the classifier system.
1,326 citations
01 Oct 1998
TL;DR: This book provides an overview of artificial immune systems, explaining its applications in areas such as immunological memory, anomaly detection algorithms, and modeling the effects of prior infection on vaccine efficacy.
Abstract: This is a pioneering work on the emerging field of artificial immune systems-highly distributed systems based on the principles of the natural system. Like artificial neural networks, artificial immune systems can learn new information and recall previously learned information. This book provides an overview of artificial immune systems, explaining its applications in areas such as immunological memory, anomaly detection algorithms, and modeling the effects of prior infection on vaccine efficacy.
1,072 citations