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Guide to Simulation and Modeling for Biosciences pp 15–78Cite as

Agent-Based Modeling

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Part of the book series: Simulation Foundations, Methods and Applications ((SFMA))

Abstract

This chapter introduces agent-based models (ABMs). These are computational semi-realistic models where every important part of the system is explicitly represented. ABMs can be very valuable in biological modeling because they can represent very complicated systems that cannot be represented using, for example, purely equation-based modeling approaches. This chapter explains the underlying ideas of ABMs, and highlights the characteristics that make systems amenable to ABM modeling. A large part comprises walk through illustrations of two models, namely, the spread of malaria in a spatially structured population and a model of the evolution of fimbriae. This last example also demonstrates how ABMs can be used to simulate evolution in a biologically realistic way.

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Notes

  1. 1.

    Concurrency denotes a situation whereby two or more processes are taking place at the same time. It is commonly used as a technical term in computer science for independent, quasi-simultaneous executions of instructions within a single program.

  2. 2.

    There are specialized algorithms available to do this, and there will be no need to re-implement them. For programmers of C/C++ the Gnu Scientific Library [5] is one place to look.

  3. 3.

    Alternative symmetrical configurations would obviously be equivalent.

  4. 4.

    We assume that the mosquitoes continue to move; if all agents were immobile, this would be a meaningless model.

  5. 5.

    We do not really assume that a single warning bird gene exists, and this expression should therefore be understood as a label for a number of genetic modifications that impact on the said behavior.

  6. 6.

    In the simulations here we used a value of 0.1 per reproduction event.

  7. 7.

    Strictly, it only shows this for this particular run, but we have found this qualitative feature confirmed over all the simulation runs we performed.

References

  1. Huse, G., Giske, J.: Ecology in Mare Pentium: an individual based spatio-temporal model for fish with adapted behaviour. Fish. Res. 37, 163–178 (1998)

    Article  Google Scholar 

  2. Bonabeau, E., Theraulaz, G., Dorigo, M.: Self-organization in social insects. Santa Fe Institute Working Paper 97-04-032 (1997)

    Google Scholar 

  3. Casti, J.: Would-Be Worlds. Wiley, New York (1997)

    Google Scholar 

  4. Ray, T.: An Approach to the Syntheses of Life. Oxford Readings in Philosophy, pp. 111–145. Oxford University Press, Oxford (1996)

    Google Scholar 

  5. Foundation, F.S.: GSL—GNU scientific library. https://www.gnu.org/software/gsl/. Accessed 22 June 2015

  6. Kohler, T., Gumerman, G.: Dynamics of Human and Primate Societies. Oxford University Press, Oxford (1999)

    Google Scholar 

  7. Bak, P.: How Nature Works. Oxford University Press, Oxford (1997)

    Google Scholar 

  8. Venables, M., Bilge, U.: Complex Adaptive Modelling at Sainsbury. Business Processes Resource Centre (1998)

    Google Scholar 

  9. Tesfatsion, L.: Agent-based computational economics: growing economies from the bottom up. Artif. Life 8(1), 55–82 (2002)

    Article  MathSciNet  Google Scholar 

  10. Wolfram, S.: Cellular Automata and Complexity. Addison-Wesley, Reading (1994)

    MATH  Google Scholar 

  11. Chu, D., Rowe, J.: Spread of vector borne diseases in a population with spatial structure. In: Proceedings of PPSN VIII—Eight International Conference on Parallel Problem Solving from Nature. Lecture Notes in Computer Science, vol. 3242, pp. 222–232. Springer, Birmingham (2004)

    Google Scholar 

  12. Dijkstra, E.W.: Chapter I: Notes on Structured Programming. Academic Press Ltd., London (1972)

    Google Scholar 

  13. Nowak, M.: Evolutionary Dynamics: Exploring the Equations of Life. Harvard University Press, Cambridge (2006)

    Google Scholar 

  14. Traulsen, A., Nowak, M.: Evolution of cooperation by multilevel selection. Proc. Natl Acad. Sci. USA 103(29), 10952–10955 (2006). doi:10.1073/pnas.0602530103

    Article  Google Scholar 

  15. Wilson, D.S.: A theory of group selection. Proc. Natl. Acad. Sci. USA 72(1), 143–146 (1975)

    Article  MATH  Google Scholar 

  16. Wilson, D.: Evolutionary biology: struggling to escape exclusively individual selection. Q. Rev. Biol. 76(2), 199–205 (2001)

    Article  Google Scholar 

  17. Sober, E., Wilson, D.: Unto Others, the Evolution and Psychology of Unselfish Behaviour. Harvard University Press, Cambridge (1998)

    Google Scholar 

  18. Gould, S.: The Structure of Evolutionary Theory. Belknap Press, Cambridge (2002)

    Google Scholar 

  19. Dawkins, R.: The Selfish Gene. University Press, Oxford (1989)

    Google Scholar 

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Authors and Affiliations

  1. University of Kent, Canterbury, Kent, UK

    David J. Barnes & Dominique Chu

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  1. David J. Barnes
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  2. Dominique Chu
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Correspondence to David J. Barnes .

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Barnes, D.J., Chu, D. (2015). Agent-Based Modeling. In: Guide to Simulation and Modeling for Biosciences. Simulation Foundations, Methods and Applications. Springer, London. https://doi.org/10.1007/978-1-4471-6762-4_2

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  • DOI: https://doi.org/10.1007/978-1-4471-6762-4_2

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-6761-7

  • Online ISBN: 978-1-4471-6762-4

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