Skip to main content
Top

2016 | OriginalPaper | Chapter

10. Artificial Immune Systems

Authors : Ke-Lin Du, M. N. S. Swamy

Published in: Search and Optimization by Metaheuristics

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

EAs and PSO tend to converge to a single optimum and hence progressively lose diversity. This is not the case for artificial immune systems (AISs). AISs are based on four main immunological theories, namely, clonal selection, immune networks, negative selection, and danger theory. This chapter introduces four immune algorithms inspired by the four immunological theories.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Ada GL, Nossal GJV. The clonal selection theory. Sci Am. 1987;257(2):50–7.CrossRef Ada GL, Nossal GJV. The clonal selection theory. Sci Am. 1987;257(2):50–7.CrossRef
2.
3.
go back to reference Burnet FM. The clonal selection theory of acquired immunity. Cambridge, UK: Cambridge University Press; 1959.CrossRef Burnet FM. The clonal selection theory of acquired immunity. Cambridge, UK: Cambridge University Press; 1959.CrossRef
4.
go back to reference Coelho GP, Von Zuben FJ. Omni-aiNet: an immune-inspired approach for omni optimization. In: Proceedings of the 5th international conference on artificial immune systems, Oeiras, Portugal, Sept 2006. p. 294–308. Coelho GP, Von Zuben FJ. Omni-aiNet: an immune-inspired approach for omni optimization. In: Proceedings of the 5th international conference on artificial immune systems, Oeiras, Portugal, Sept 2006. p. 294–308.
5.
go back to reference Cutello V, Nicosia G, Pavone M. An immune algorithm with stochastic aging and Kullback entropy for the chromatic number problem. J Combinator Optim. 2007;14(1):9–33.MathSciNetCrossRefMATH Cutello V, Nicosia G, Pavone M. An immune algorithm with stochastic aging and Kullback entropy for the chromatic number problem. J Combinator Optim. 2007;14(1):9–33.MathSciNetCrossRefMATH
6.
go back to reference Dasgupta D. Advances in artificial immune systems. IEEE Comput Intell Mag. 2006;1(4):40–9.CrossRef Dasgupta D. Advances in artificial immune systems. IEEE Comput Intell Mag. 2006;1(4):40–9.CrossRef
7.
go back to reference de Castro PAD, Von Zuben FJ. BAIS: a Bayesian artificial immune system for the effective handling of building blocks. Inf Sci. 2009;179(10):1426–40. de Castro PAD, Von Zuben FJ. BAIS: a Bayesian artificial immune system for the effective handling of building blocks. Inf Sci. 2009;179(10):1426–40.
8.
go back to reference de Castro LN, Timmins J. An artificial immune network for multimodal function optimization. In: Proceedings of IEEE congress on evolutionary computation, Honolulu, HI, USA, May 2002, vol. 1, p. 699–704. de Castro LN, Timmins J. An artificial immune network for multimodal function optimization. In: Proceedings of IEEE congress on evolutionary computation, Honolulu, HI, USA, May 2002, vol. 1, p. 699–704.
9.
go back to reference de Castro LN, Von Zuben FJ. aiNet: an artificial immune network for data analysis. In: Abbass HA, Sarker RA, Newton CS, editors. Data mining: a heuristic approach. Hershey, USA: Idea Group Publishing; 2001. p. 231–259. de Castro LN, Von Zuben FJ. aiNet: an artificial immune network for data analysis. In: Abbass HA, Sarker RA, Newton CS, editors. Data mining: a heuristic approach. Hershey, USA: Idea Group Publishing; 2001. p. 231–259.
10.
go back to reference de Castro LN, Von Zuben FJ. Learning and optimization using the clonal selection principle. IEEE Trans Evol Comput. 2002;6(3):239–51.CrossRef de Castro LN, Von Zuben FJ. Learning and optimization using the clonal selection principle. IEEE Trans Evol Comput. 2002;6(3):239–51.CrossRef
11.
go back to reference de Franca FO, Von Zuben FJ, de Castro LN. An artificial immune network for multimodal function optimization on dynamic environments. In: Proceedings of genetic and evolutionary computation conference (GECCO), Washington, DC, USA, June 2005. p. 289–296. de Franca FO, Von Zuben FJ, de Castro LN. An artificial immune network for multimodal function optimization on dynamic environments. In: Proceedings of genetic and evolutionary computation conference (GECCO), Washington, DC, USA, June 2005. p. 289–296.
12.
go back to reference Engelbrecht AP. Computational intelligence: an introduction. New York: Wiley; 2007.CrossRef Engelbrecht AP. Computational intelligence: an introduction. New York: Wiley; 2007.CrossRef
13.
go back to reference Ferreira C. Gene expression programming: a new adaptive algorithm for solving problems. Complex Syst. 2001;13(2):87–129.MathSciNetMATH Ferreira C. Gene expression programming: a new adaptive algorithm for solving problems. Complex Syst. 2001;13(2):87–129.MathSciNetMATH
14.
go back to reference Forrest S, Perelson AS, Allen L, Cherukuri R. Self-nonself discrimination in a computer. In: Proceedings of IEEE symposium on security and privacy, Oakland, CA, USA, May 1994. p. 202–212. Forrest S, Perelson AS, Allen L, Cherukuri R. Self-nonself discrimination in a computer. In: Proceedings of IEEE symposium on security and privacy, Oakland, CA, USA, May 1994. p. 202–212.
15.
go back to reference Forrest S, Hofmeyr SA, Somayaji A. Computer immunology. Commun ACM. 1997;40(10):88–96.CrossRef Forrest S, Hofmeyr SA, Somayaji A. Computer immunology. Commun ACM. 1997;40(10):88–96.CrossRef
16.
go back to reference Garret SM. Parameter-free, adaptive clonal selection. In: Proceedings of IEEE congress on evolutionary computation (CEC), Portland, OR, June 2004. p. 1052–1058. Garret SM. Parameter-free, adaptive clonal selection. In: Proceedings of IEEE congress on evolutionary computation (CEC), Portland, OR, June 2004. p. 1052–1058.
17.
go back to reference Greensmith J, Aickelin U. Dendritic cells for SYN scan detection. In: Proceedings of genetic and evolutionary computation conference (GECCO), London, UK, July 2007. p. 49–56. Greensmith J, Aickelin U. Dendritic cells for SYN scan detection. In: Proceedings of genetic and evolutionary computation conference (GECCO), London, UK, July 2007. p. 49–56.
18.
go back to reference Greensmith J, Aickelin U. The deterministic dendritic cell algorithm. In: Proceedings of the 7th International conference on artificial immune systems (ICARIS), Phuket, Thailand, August 2008. p. 291–303. Greensmith J, Aickelin U. The deterministic dendritic cell algorithm. In: Proceedings of the 7th International conference on artificial immune systems (ICARIS), Phuket, Thailand, August 2008. p. 291–303.
19.
go back to reference Greensmith J, Aickelin U, Cayzer S. Introducing dendritic cells as a novel immune-inspired algorithm for anomaly detection. In: Proceedings of the 4th international conference on artificial immune systems (ICARIS), Banff, Alberta, Canada, Aug 2005. p. 153–167. Greensmith J, Aickelin U, Cayzer S. Introducing dendritic cells as a novel immune-inspired algorithm for anomaly detection. In: Proceedings of the 4th international conference on artificial immune systems (ICARIS), Banff, Alberta, Canada, Aug 2005. p. 153–167.
20.
go back to reference Hofmeyr SA, Forrest S. Architecture for an artificial immune system. Evol Comput. 2000;8(4):443–73.CrossRef Hofmeyr SA, Forrest S. Architecture for an artificial immune system. Evol Comput. 2000;8(4):443–73.CrossRef
21.
go back to reference Jerne NK. Towards a network theory of the immune system. Annales d’Immunologie (Paris). 1974;125C:373–89. Jerne NK. Towards a network theory of the immune system. Annales d’Immunologie (Paris). 1974;125C:373–89.
22.
go back to reference Jiao L, Wang L. A novel genetic algorithm based on immunity. IEEE Trans Syst Man Cybern Part A. 2000;30(5):552–61.CrossRef Jiao L, Wang L. A novel genetic algorithm based on immunity. IEEE Trans Syst Man Cybern Part A. 2000;30(5):552–61.CrossRef
23.
go back to reference Matzinger P. Tolerance, danger and the extended family. Annu Rev Immunol. 1994;12:991–1045.CrossRef Matzinger P. Tolerance, danger and the extended family. Annu Rev Immunol. 1994;12:991–1045.CrossRef
24.
go back to reference Matzinger P. The danger model: a renewed sense of self. Science. 2002;296(5566):301–5.CrossRef Matzinger P. The danger model: a renewed sense of self. Science. 2002;296(5566):301–5.CrossRef
25.
go back to reference Owens NDL, Greensted A, Timmis J, Tyrrell A. T cell receptor signalling inspired kernel density estimation and anomaly detection. In: Proceedings of the 8th international conference on artificial immune systems (ICARIS), York, UK, Aug 2009. p. 122–135. Owens NDL, Greensted A, Timmis J, Tyrrell A. T cell receptor signalling inspired kernel density estimation and anomaly detection. In: Proceedings of the 8th international conference on artificial immune systems (ICARIS), York, UK, Aug 2009. p. 122–135.
26.
27.
go back to reference Smith RE, Forrest S, Perelson AS. Population diversity in an immune system model: implications for genetic search. In: Whitley LD, editor. Foundations of genetic algorithms, vol. 2. San Mateo, CA: Morgan Kaufmann Publishers; 1993. p. 153–165. Smith RE, Forrest S, Perelson AS. Population diversity in an immune system model: implications for genetic search. In: Whitley LD, editor. Foundations of genetic algorithms, vol. 2. San Mateo, CA: Morgan Kaufmann Publishers; 1993. p. 153–165.
28.
go back to reference Tang T, Qiu J. An improved multimodal artificial immune algorithm and its convergence analysis. In: Proceedings of world congress on intelligent control and automation, Dalian, China, June 2006. p. 3335–3339. Tang T, Qiu J. An improved multimodal artificial immune algorithm and its convergence analysis. In: Proceedings of world congress on intelligent control and automation, Dalian, China, June 2006. p. 3335–3339.
29.
go back to reference Varela F, Sanchez-Leighton V, Coutinho A. Adaptive strategies gleaned from immune networks: Viability theory and comparison with classifier systems. In: Goodwin B, Saunders PT, editors. Theoretical biology: epigenetic and evolutionary order (a Waddington Memorial Conference). Edinburgh, UK: Edinburgh University Press; 1989. p. 112–123. Varela F, Sanchez-Leighton V, Coutinho A. Adaptive strategies gleaned from immune networks: Viability theory and comparison with classifier systems. In: Goodwin B, Saunders PT, editors. Theoretical biology: epigenetic and evolutionary order (a Waddington Memorial Conference). Edinburgh, UK: Edinburgh University Press; 1989. p. 112–123.
30.
go back to reference Woldemariam KM, Yen GG. Vaccine-enhanced artificial immune system for multimodal function optimization. IEEE Trans Syst Man Cybern Part B. 2010;40(1):218–28.CrossRef Woldemariam KM, Yen GG. Vaccine-enhanced artificial immune system for multimodal function optimization. IEEE Trans Syst Man Cybern Part B. 2010;40(1):218–28.CrossRef
31.
go back to reference Xu X, Zhang J. An improved immune evolutionary algorithm for multimodal function optimization. In: Proceedings of the 6th international conference on natural computing, Haikou, China, Aug 2007. p. 641–646. Xu X, Zhang J. An improved immune evolutionary algorithm for multimodal function optimization. In: Proceedings of the 6th international conference on natural computing, Haikou, China, Aug 2007. p. 641–646.
32.
go back to reference Zhang R, Li T, Xiao X, Shi Y. A danger-theory-based immune network optimization algorithm. Sci World J;2013:Article ID 810320, 13 p. Zhang R, Li T, Xiao X, Shi Y. A danger-theory-based immune network optimization algorithm. Sci World J;2013:Article ID 810320, 13 p.
Metadata
Title
Artificial Immune Systems
Authors
Ke-Lin Du
M. N. S. Swamy
Copyright Year
2016
DOI
https://doi.org/10.1007/978-3-319-41192-7_10

Premium Partner