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Computational Laboratories for Spatial Agent-Based Models

In: Handbook of Computational Economics


  • Dibble, Catherine


An agent-based model is a virtual world comprising distributed heterogeneous agents who interact over time. In a spatial agent-based model the agents are situated in a spatial environment and are typically assumed to be able to move in various ways across this environment. Some kinds of social or organizational systems may also be modeled as spatial environments, where agents move from one group or department to another and where communications or mobility among groups may be structured according to implicit or explicit channels or transactions costs.This chapter focuses on the potential usefulness of computational laboratories for spatial agent-based modeling. Speaking broadly, a computational laboratory is any computational framework permitting the exploration of the behaviors of complex systems through systematic and replicable simulation experiments. By that definition, most of the research discussed in this handbook would be considered to be work with computational laboratories. A narrower definition of computational laboratory (or comp lab for short) refers specifically to specialized software tools to support the full range of agent-based modeling and complementary tasks. These tasks include model development, model evaluation through controlled experimentation, and both the descriptive and normative analysis of model outcomes.The objective of this chapter is to explore how comp lab tools and activities facilitate the systematic exploration of spatial agent-based models embodying complex social processes critical for social welfare. Examples include the spatial and temporal coordination of human activities, the diffusion of new ideas or of infectious diseases, and the emergence and ecological dynamics of innovative ideas or of deadly new diseases.

Suggested Citation

  • Dibble, Catherine, 2006. "Computational Laboratories for Spatial Agent-Based Models," Handbook of Computational Economics,in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 31, pages 1511-1548 Elsevier.
  • Handle: RePEc:eee:hecchp:2-31

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    Cited by:

    1. Ge, Houtian & Gray, Richard & Nolan, James, 2015. "Agricultural supply chain optimization and complexity: A comparison of analytic vs simulated solutions and policies," International Journal of Production Economics, Elsevier, vol. 159(C), pages 208-220.
    2. Setterfield, Mark & Gouri Suresh, Shyam, 2016. "Multi-agent systems as a tool for analyzing path-dependent macrodynamics," Structural Change and Economic Dynamics, Elsevier, vol. 38(C), pages 25-37.
    3. Wendel, Stephen & Oppenheimer, Joe, 2010. "An agent-based analysis of context-dependent preferences," Journal of Economic Psychology, Elsevier, vol. 31(3), pages 269-284, June.

    More about this item

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques


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