Skip to main content
SpringerLink
Log in

Designing, Formulating, and Communicating Agent-Based Models

  • Chapter
  • First Online:
Agent-Based Models of Geographical Systems

Abstract

Designing, formulating, and communicating agent-based models (ABMs) poses unique challenges, especially how to choose the right level of complexity and how to describe – and, even, think about – a model in a way that captures both its essential characteristics and its complete detail. Two techniques for dealing with such challenges have become established among agent-based modellers. The “ODD” (Overview, Design concepts, Details) protocol is a standard for describing ABMs in publications, but also provides design patterns for the model developer. ODD starts with an overview of what the model is and does, and then describes how the model implements ten “design concepts” that capture essential and unique characteristics of ABMs. Last come all the details needed to completely replicate the model. “Pattern-oriented modelling” (POM) is a set of strategies for using patterns observed in the systems to ensure that an ABM captures the right “essence” of the system. POM starts with identifying multiple patterns of behaviour in the real system and its agents that seem to capture the essential internal mechanisms for the problem being modelled. These patterns are then used to decide what kinds of entities, state variables, and processes need to be in the model; compare and test alternative “theory” for key agent behaviours; and filter potential parameter values to limit uncertainty. ODD and POM are important steps toward the acceptance of agent-based approaches as established, credible ways to do science.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 299.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 379.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 379.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Batty, M. (2005). Cities and complexity: Understanding cities through cellular automata, agent-based models, and fractals. Boston: The MIT Press.

    Google Scholar 

  • Berger, U., & Hildenbrandt, H. (2000). A new approach to spatially explicit modelling of forest dynamics: Spacing, ageing and neighbourhood competition of mangrove trees. Ecological Modelling, 132, 287–302.

    Article  Google Scholar 

  • Brown, D. G., Page, S. E., Riolo, R., & Rand, W. (2004). Agent-based and analytical modeling to evaluate the effectiveness of greenbelts. Environmental Modelling and Software, 19, 1097–1109.

    Article  Google Scholar 

  • Brown, D. G., Page, S. E., Riolo, R., Zellner, M., & Rand, W. (2005). Path dependence and the validation of agent-based spatial models of land use. International Journal of Geographic Information Systems, 19, 153–174.

    Article  Google Scholar 

  • Czárán, T. (1998). Spatiotemporal models of population and community dynamics. London: Chapman & Hall.

    Google Scholar 

  • DeAngelis, D. L., & Mooij, W. M. (2003). In praise of mechanistically-rich models. In C. D. Canham, J. J. Cole, & W. K. Lauenroth (Eds.), Models in ecosystem science (pp. 63–82). Princeton: Princeton University Press.

    Google Scholar 

  • Enquist, B. J., Brown, J. H., & West, G. B. (1998). Allometric scaling of plant energetics and population density. Nature, 395, 163–165.

    Article  Google Scholar 

  • Galvão, V., & Miranda, J. G. V. (2009). Modeling the Chagas’ disease after stem cell transplantation. Physica A, 388, 1747–1754.

    Article  Google Scholar 

  • Gamma, E., Helm, R., Johnson, R., & Vlissides, J. (1994). Design patterns: Elements of reusable object-oriented software. Reading: Addison-Wesley.

    Google Scholar 

  • Gilbert, N. (2008). Agent-based models. Quantitative applications in the social sciences. Thousand Oaks: Sage.

    Google Scholar 

  • Goss-Custard, J., Burton, N. H. K., Clark, N. A., Ferns, P. N., McGrorty, S., Reading, C. J., Rehfisch, M. M., Stillman, R. A., Townend, I., West, A. D., & Worrall, D. H. (2006). Test of a behavior-based individual-based model: Response of shorebird mortality to habitat loss. Ecological Applications, 16, 2215–2222.

    Article  Google Scholar 

  • Gotts, N. M., Polhill, J. G., & Law, A. N. R. (2003). Aspiration levels in a land use simulation. Cybernetics and Systems, 34, 663–683.

    Article  Google Scholar 

  • Grimm, V., & Railsback, S. F. (2005). Individual-based modeling and ecology. Princeton: Princeton University Press.

    Google Scholar 

  • Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., Thulke, H.-H., Weiner, J., Wiegand, T., & DeAngelis, D. L. (2005). Pattern-oriented modeling of agent-based complex systems: Lessons from ecology. Science, 310, 987–991.

    Article  Google Scholar 

  • Grimm, V., Berger, U., Bastiansen, F., et al. (2006). A standard protocol for describing individual-based and agent-based models. Ecological Modelling, 198, 115–126.

    Article  Google Scholar 

  • Grimm, V., Berger, U., DeAngelis, D. L., Polhill, G., Giske, J., & Railsback, S. F. (2010). The ODD protocol for describing individual-based and agent-based models: A first update. Ecological Modelling, 221(23), 2760–2768. doi:10.1016/j.ecolmodel.2010.08.019.

    Article  Google Scholar 

  • Guzy, M.R., Smith, C.L., Bolte, J. P., Hulse, D. W., & Gregory, S. V. (2008). Policy research using agent-based modeling to assess future impacts of urban expansion into farmlands and forests. Ecology and Society, 13, 37. [online] URL: http://www.ecologyandsociety.org/vol13/iss1/art37/

  • Hales, D., Rouchier, J., Edmonds, B. (2003). Model-to-model analysis. Journal of Artificial Societies and Social Simulation, 6, URL: http://jasss.soc.surrey.ac.uk/6-4/5.html

  • Heine, B.-O., Meyer, M., & Strangfeld, O. (2007). Das Konzept der stilisierten Fakten zur Messung und Bewertung wissenschaftlichen Fortschritts. Die Betriebswirtschaft, 67, 583–608.

    Google Scholar 

  • Hellweger, F. L., Kravchuk, E. S., Novotny, V., & Gladyshev, M. I. (2008). Agent-based modeling of the complex life cycle of a cyanobacterium (Anabaena) in a shallow reservoir. Limnology and Oceanography, 53, 1227–1241.

    Article  Google Scholar 

  • Janssen, M. A., Alessa, L. N., Barton, M., Bergin, S., & Lee, A. (2008). Towards a community framework for agent-based modelling. Journal of Artificial Societies and Social Simulation, 11(2), 6. http://jasss.soc.surrey.ac.uk/11/2/6.html.

    Google Scholar 

  • Janssen, M. A., Radtke, N. P., & Lee, A. (2009). Pattern-oriented modeling of common dilemma experiments. Adaptive Behavior, 17(6), 508–523. doi:10.1177/1059712309342488.

    Article  Google Scholar 

  • Kaldor, N. (1961). Capital accumulation and economic growth. In F. A. Lutz & D. C. Hague (Eds.), The theory of capital (pp. 177–222). London: Macmillan.

    Google Scholar 

  • Parker, D. C. (1999). Landscape outcomes in a model of edge-effect externalities: A computational economics approach. SFI Publication 99-07-051. Santa Fe: Santa Fe Institute. http://www.santafe.edu/sfi/publications/Working-Papers/99-07-051.pdf

  • Parker, D. C., & Meretsky, V. (2004). Measuring pattern outcomes in an agent-based model of edge-effect externalities using spatial metrics. Agriculture, Ecosystems and Environment, 101, 233–250.

    Article  Google Scholar 

  • Piou, C., Berger, U., & Grimm, V. (2009). Proposing an information criterion for individual-based models developed in a pattern-oriented framework. Ecological Modelling, 220, 1957–1967.

    Article  Google Scholar 

  • Platt, J. R. (1964). Strong inference. Science, 146, 347–353.

    Article  Google Scholar 

  • Polhill, J. G., Gotts, N. M., & Law, A. N. R. (2001). Imitative versus nonimitative strategies in a land use simulation. Cybernetics and Systems, 32, 285–307.

    Article  Google Scholar 

  • Polhill, J. G., Parker, D. C., & Gotts, N. M. (2005). Introducing land markets to and agent based models of land use change. In K. G. Troitzsch (Ed.), Representing social reality: Pre-proceedings of the third conference of the European Social Simulation Association (pp. 150–157). Koblenz: Dietmar Fölbach.

    Google Scholar 

  • Polhill, J. G., Brown, D. G., & Grimm, V. (2008a). Using the ODD protocol for describing three agent-based social simulation models of land use change. Journal of Artificial Societies and Social Simulation, 11 URL: http://jasss.soc.surrey.ac.uk/11-2/3.html

  • Polhill, J. G., Parker, D. C., & Gotts, N. M. (2008b). Effects of land markets on competition between innovators and imitators in land use: Results from FEARLUS-ELMM. In C. Hernandez, K. Troitzsch, & B. Edmonds (Eds.), Social simulation technologies: Advances and new discoveries (pp. 81–97). New York: IGI Global.

    Google Scholar 

  • Premo, L. S., & Hublin, J.-J. (2009). Culture, population structure, and low genetic diversity in Pleistocene hominins. PNAS, 106, 33–37.

    Article  Google Scholar 

  • Rademacher, C., Neuert, C., Grundmann, V., et al. (2001). Was charakterisiert Buchenurwälder? Untersuchungen der Altersstruktur des Kronendachs und der räumlichen Verteilung der Baumriesen mit Hilfe des Simulationsmodells BEFORE. Forstwiss Centralbl, 120, 288–302.

    Article  Google Scholar 

  • Rademacher, C., Neuert, C., Grundmann, V., et al. (2004). Reconstructing spatiotemporal dynamics of Central European natural beech forests: The rule-based forest model BEFORE. Forest Ecology and Management, 194, 349–368.

    Article  Google Scholar 

  • Railsback, S. F. (2001). Concepts from complex adaptive systems as a framework for individual-based modelling. Ecological Modelling, 139, 47–62.

    Article  Google Scholar 

  • Railsback, S. F., & Harvey, B. C. (2002). Analysis of habitat-selection rules using an individual-based model. Ecology, 83, 1817–1830.

    Google Scholar 

  • Richiardi, M., Leombruni, R., Saam, N., & Sonnessa, M. (2006). A common protocol for agent-based social simulation. Journal of Artificial Societies and Social Simulation, 9, URL: http://jasss.soc.surrey.ac.uk/9/1/15.html

  • Schelling, T. C. (1971). Dynamic models of segregation. Journal of Mathematical Sociology, 1, 143–186.

    Article  Google Scholar 

  • Thiery, J. M., D’Herbes, J. M., & Valentin, C. (1995). A model simulating the genesis of banded vegetation patterns in Niger. Journal of Ecology, 83, 497–507.

    Article  Google Scholar 

  • Watson, J. (1968). The double helix: A personal account of the discovery of the structure of DNA. New York: Atheneum.

    Google Scholar 

  • Wiegand, T., Revilla, E., & Knauer, F. (2004). Dealing with uncertainty in spatially explicit population models. Biodiversity and Conservation, 13, 53–78.

    Article  Google Scholar 

  • Wikipedia (2009). Software design patterns. July 24, 2009. URL: http://en.wikipedia.org/wiki/Software_design_patterns

  • Wilensky, U. (1997). NetLogo segregation model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston. http://ccl.northwestern.edu/netlogo/models/Segregation

Download references

Author information

Authors and Affiliations

  1. Department of Ecological Modelling, Helmholtz Center for Environmental Research - UFZ, Leipzig, Germany

    Volker Grimm

  2. Department of Mathematics, Humboldt State University, Arcata, CA, USA

    Steven F. Railsback

Authors
  1. Volker Grimm
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Steven F. Railsback
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Volker Grimm .

Editor information

Editors and Affiliations

  1. School of Geography, University of Leeds, Woodhouse Lane, Leeds, LS2 9JT, United Kingdom

    Alison J. Heppenstall

  2. , Department of Computational Social Scien, George Mason University, University Drive 4400, Fairfax, 22030, Virginia, USA

    Andrew T. Crooks

  3. International Institute of Applied Syste, Schlossplatz 1, Laxenburg, 2361, Austria

    Linda M. See

  4. Ctr. Advanced Spatial Analysis, University College London, Torrington Place 1-19, London, WC1E 6BT, United Kingdom

    Michael Batty

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Grimm, V., Railsback, S.F. (2012). Designing, Formulating, and Communicating Agent-Based Models. In: Heppenstall, A., Crooks, A., See, L., Batty, M. (eds) Agent-Based Models of Geographical Systems. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8927-4_17

Download citation

Publish with us

Policies and ethics

Search

Navigation