Inferring Equation-Based Models from Agent-Based Models: A Case Study in Competition Dynamics

  • Ngoc Doanh Nguyen
  • Patrick Taillandier
  • Alexis Drogoul
  • Pierre Auger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7057)

Abstract

Two types of model, equation-based models (EBMs) and agent-based models (ABMs) are now widely used in modeling ecological complex systems and seem not to be reconciled. While ABMs can help in exploring and explaining the local causes of global phenomena, EBMs are useful for predicting their long-term evolution without having to explore them through simulated experiments. In this paper, we show that it is possible to use an ABM to infer an EBM. Base on the case study, a dynamics of two competing species, we illustrate our methodology through the presentation of two models: an ABM and an EBM. We also show that the two models give the same results on coexistence of the two competing species.

Keywords

Agent-Based Models Equation-Based Models Population Dynamics Complex Systems 

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References

  1. 1.
    Fahse, L., Wissel, C., Grimm, V.: Reconciling classical and individual-based aprroahes in theoretical population ecology: a protocol for extracting population parameters from individual-based models. American Naturalist 152, 838–852 (1998)Google Scholar
  2. 2.
    Nguyen, N.D., Drogoul, A., Auger, P.: Methodological Steps and Issues When Deriving Individual Based-Models from Equation-Based Models: A Case Study in Population Dynamics. In: Bui, T.D., Ho, T.V., Ha, Q.T. (eds.) PRIMA 2008. LNCS (LNAI), vol. 5357, pp. 295–306. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  3. 3.
    Murray, J.D.: Mathematical Biology. Springer, Heidelberg (1989)CrossRefMATHGoogle Scholar
  4. 4.
    Auger, P., Bravo de la Parra, R., Poggiale, J.C., Sánchez, E., Nguyen Huu, T.: Aggregation of variables and applications to population dynamics. In: Magal, P., Ruan, S. (eds.) Structured Population Models in Biology and Epidemiology, Springer, Heidelberg (2008)Google Scholar
  5. 5.
    Grimm, V., Railsback, S.F.: Individual-based Modeling and Ecology. Princeton University Press (2005)Google Scholar
  6. 6.
    Laubenbacher, R., Jarrah, A.S., Mortveit, H., Ravi, S.S.: A mathematical formalism for agent-based modeling, arXiv:08.01.0249v1 [cs. MA] (2007); Fahse, L., Wissel, C., Grimm, V.: Reconciling classical and individual-based aprroahes in theoretical population ecology: a protocol for extracting population parameters from individual-based models. American Naturalist 152, 838–852 (1998)Google Scholar
  7. 7.
    Law, R., Dieckmann, U.: Moment approximations of individual-based models (1999), http://www.iiasa.ac.at/Admin/PUB/Documents/IR-99-043.pdf
  8. 8.
    Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S.K., Huse, G., Huth, A., Jepsen, J.U., Jørgensen, C., Mooij, W.M., Müller, B., Pe’er, G., Piou, C., Railsback, S.F., Robbins, A.M., Robbins, M.M., Rossmanith, E., Rüger, N., Strand, E., Souissi, S., Stillman, R.A., Vabo, R., Visser, U., DeAngelis, D.L.: A standard protocol for describing individual-based and agent-based models. Ecological Modelling 198(1-2), 115–126 (2006)CrossRefGoogle Scholar
  9. 9.
    Amouroux, E., Chu, T.-Q., Boucher, A., Drogoul, A.: GAMA: An Environment for Implementing and Running Spatially Explicit Multi-Agent Simulations. In: Ghose, A., Governatori, G., Sadananda, R. (eds.) PRIMA 2007. LNCS, vol. 5044, pp. 359–371. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  10. 10.
    Luke, S., Cioffi-Revilla, C., Panait, L., Sullivan, K., Balan, G.: MASON: a multiagent simulation environment. Simulation 81, 517–527 (2005)CrossRefGoogle Scholar
  11. 11.
    North, M.J., Collier, N.T., Vos, J.R.: Experiences Creating Three Implementations of the Repast Agent Modeling Toolkit. ACM Transactions on Modeling and Computer Simulation 16(1), 1–25 (2006)CrossRefGoogle Scholar
  12. 12.
    Tisue, S., Wilensky. U.: NetLogo: A Simple Environment for Modeling Complexity. In: ICCS (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ngoc Doanh Nguyen
    • 1
    • 2
  • Patrick Taillandier
    • 1
    • 2
  • Alexis Drogoul
    • 1
    • 2
  • Pierre Auger
    • 2
    • 3
  1. 1.MSI, IFIHanoiVietnam
  2. 2.UMMISCO, UMI 209, IRD/UPMCBondy CedexFrance
  3. 3.LMPD, University Cadi AyyadMarrakechMorocco

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