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Systems Dynamics or Agent-Based Modelling for Immune Simulation?

  • Grazziela P. Figueredo
  • Uwe Aickelin
  • Peer-Olaf Siebers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6825)

Abstract

In immune system simulation there are two competing simulation approaches: System Dynamics Simulation (SDS) and Agent-Based Simulation (ABS). In the literature there is little guidance on how to choose the best approach for a specific immune problem. Our overall research aim is to develop a framework that helps researchers with this choice. In this paper we investigate if it is possible to easily convert simulation models between approaches. With no explicit guidelines available from the literature we develop and test our own set of guidelines for converting SDS models into ABS models in a non-spacial scenario. We also define guidelines to convert ABS into SDS considering a non-spatial and a spatial scenario. After running some experiments with the developed models we found that in all cases there are significant differences between the results produced by the different simulation methods.

Keywords

Tumour Cell Population Proactive Behaviour State Chart Explicit Guideline Immune Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Grazziela P. Figueredo
    • 1
  • Uwe Aickelin
    • 1
  • Peer-Olaf Siebers
    • 1
  1. 1.Intelligent Modelling and Analysis Research Group, School of Computer ScienceThe University of NottinghamUK

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