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A Game-Theoretic Approach to Artificial Immune Networks

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3239))

Abstract

In this paper, a well-known evolutionary dynamics, replicator dynamics, is used to model the dynamics of an immune network. A doubly symmetric game is associated to an immune network by this model, which implies some optimal behavior throughout time under replicator dynamics. Stability of an immune network is guaranteed by such dynamics. Two types of immune networks were modeled. In addition, an algorithm in which perturbation of an immune network by a set of antigens to be recognized is proposed. Some preliminary experiments were carried out to show the potentials of the model.

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© 2004 Springer-Verlag Berlin Heidelberg

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Velez, M., Nino, F., Alonso, O.M. (2004). A Game-Theoretic Approach to Artificial Immune Networks. In: Nicosia, G., Cutello, V., Bentley, P.J., Timmis, J. (eds) Artificial Immune Systems. ICARIS 2004. Lecture Notes in Computer Science, vol 3239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30220-9_30

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  • DOI: https://doi.org/10.1007/978-3-540-30220-9_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23097-7

  • Online ISBN: 978-3-540-30220-9

  • eBook Packages: Springer Book Archive

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