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Immune Responses: A Stochastic Model

  • Conference paper
Artificial Immune Systems (ICARIS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5132))

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Abstract

Immune phenomena are explained from the reductionist view of the immune system as a collection of cells, molecules, and their interactions. Although this approach has produced abundant valuable information, it has added increased complexity. Artificial Immune Systems (AIS) have relied on this theoretical framework to emulate the desired characteristics of immunity. However, the complexity of the theoretical base has lead to an impasse in AIS research, suggesting that a new theoretical framework is needed. A theoretical model is presented here that explains immune responses as a ”swarm function”. The model proposes a system based on two stochastic networks: a central recursive network, wherein the proportion of agents is determined and maintained, and a peripheral network, wherein the random interactions of these agents determine if an inflammatory response will emerge from the system.

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Authors and Affiliations

  1. Hotchkiss Brain Institute,  

    Anastasio Salazar-Bañuelos

  2. Department of Surgery, Division of Transplantation, University of Calgary, AB, Canada

    Anastasio Salazar-Bañuelos

Authors
  1. Anastasio Salazar-Bañuelos
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Editor information

Peter J. Bentley Doheon Lee Sungwon Jung

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© 2008 Springer-Verlag Berlin Heidelberg

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Salazar-Bañuelos, A. (2008). Immune Responses: A Stochastic Model. In: Bentley, P.J., Lee, D., Jung, S. (eds) Artificial Immune Systems. ICARIS 2008. Lecture Notes in Computer Science, vol 5132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85072-4_3

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  • DOI: https://doi.org/10.1007/978-3-540-85072-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85071-7

  • Online ISBN: 978-3-540-85072-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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