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The GeoGraph 3D Computational Laboratory: Network and Terrain Landscapes for RePast

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Abstract

Our GeoGraph 3D extensions to the RePast agent-based simulation platform support models in which mobile agents travel and interact on rugged terrain or on network landscapes such as social networks of established organizational teams or spatial networks at any scale from rooms within buildings to urban neighborhoods to large geographic networks of cities. Interactive GeoGraph 3D visualizations allow researchers to zoom and pan within the simulation landscape as the model runs. Model-specific 3D representations of agents flock together on terrain landscapes, and teleport or travel along links on network landscapes. Agents may be displayed on network nodes either as individual agents or as dynamic 3D bar charts that reflect the composition of each node's population. Batch modes support scientific control via fully separated random number series, customized parameter combinations, and automatic data collection for many thousands of simulation runs. This paper introduces the GeoGraph 3D computational laboratory and briefly describes three representative GeoGraph models along with basic GeoGraph 3D capabilities and components.

Suggested Citation

  • Catherine Dibble & Philip G. Feldman, 2004. "The GeoGraph 3D Computational Laboratory: Network and Terrain Landscapes for RePast," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 7(1), pages 1-7.
    • Handle: RePEc:jas:jasssj:2004-3-1
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    File URL: http://jasss.soc.surrey.ac.uk/7/1/7.html
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    Cited by:

    1. Fioretti, Guido, 2010. "Trajectories in Physical Space out of Communications in Acquaintance Space: An Agent-Based Model of a Textile Industrial District," MPRA Paper 24902, University Library of Munich, Germany.
    2. András Bóta & Lauren M. Gardner & Alireza Khani, 2017. "Identifying Critical Components of a Public Transit System for Outbreak Control," Networks and Spatial Economics, Springer, vol. 17(4), pages 1137-1159, December.
    3. Jill Bigley Dunham, 2005. "An Agent-Based Spatially Explicit Epidemiological Model in MASON," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-3.
    4. David Fajardo & Lauren Gardner, 2013. "Inferring Contagion Patterns in Social Contact Networks with Limited Infection Data," Networks and Spatial Economics, Springer, vol. 13(4), pages 399-426, December.
    5. Rakowski, Franciszek & Gruziel, Magdalena & Bieniasz-Krzywiec, Łukasz & Radomski, Jan P., 2010. "Influenza epidemic spread simulation for Poland — a large scale, individual based model study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3149-3165.

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