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Artificial Immune Systems

In: Search and Optimization by Metaheuristics

Author

Listed:
  • Ke-Lin Du

    (Xonlink Inc
    Concordia University, Department of Electrical and Computer Engineering)

  • M. N. S. Swamy

    (Concordia University, Department of Electrical and Computer Engineering)

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.

Suggested Citation

  • Ke-Lin Du & M. N. S. Swamy, 2016. "Artificial Immune Systems," Springer Books, in: Search and Optimization by Metaheuristics, chapter 0, pages 175-189, Springer.
  • Handle: RePEc:spr:sprchp:978-3-319-41192-7_10
    DOI: 10.1007/978-3-319-41192-7_10
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