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Building, composing and experimenting complex spatial models with the GAMA platform

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Abstract

The agent-based modeling approach is now used in many domains such as geography, ecology, or economy, and more generally to study (spatially explicit) socio-environmental systems where the heterogeneity of the actors and the numerous feedback loops between them requires a modular and incremental approach to modeling. One major reason of this success, besides this conceptual facility, can be found in the support provided by the development of increasingly powerful software platforms, which now allow modelers without a strong background in computer science to easily and quickly develop their own models. Another trend observed in the latest years is the development of much more descriptive and detailed models able not only to better represent complex systems, but also answer more intricate questions. In that respect, if all agent-based modeling platforms support the design of small to mid-size models, i.e. models with little heterogeneity between agents, simple representation of the environment, simple agent decision-making processes, etc., very few are adapted to the design of large-scale models. GAMA is one of the latter. It has been designed with the aim of supporting the writing (and composing) of fairly complex models, with a strong support of the spatial dimension, while guaranteeing non-computer scientists an easy access to high-level, otherwise complex, operations. This paper presents GAMA 1.8, the latest revision to date of the platform, with a focus on its modeling language and its capabilities to manage the spatial dimension of models. The capabilities of GAMA are illustrated by the presentation of applications that take advantage of its new features.

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  1. https://github.com/gama-platform/gama

  2. https://groups.google.com/forum/#!forum/gama-platform

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Authors and Affiliations

  1. MIAT, University of Toulouse, INRA, 31320, Castanet-Tolosan, France

    Patrick Taillandier

  2. IRIT, University of Toulouse, CNRS, INPT, UPS, UT1, UT2J, Toulouse, France

    Benoit Gaudou

  3. UMMISCO, IRD, Sorbonne University, F-93143, Bondy, France

    Benoit Gaudou, Nicolas Marilleau & Alexis Drogoul

  4. ICTLab, USTH, Hanoi, Vietnam

    Benoit Gaudou

  5. MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA

    Arnaud Grignard

  6. DREAM-CTU/IRD, CICT-CTU, Cantho, Vietnam

    Quang-Nghi Huynh

  7. LRI - INRIA TAU, University Paris Sud, Gif sur Yvette, France

    Philippe Caillou

  8. School of Public Health, University of Hong Kong, Hong Kong, China

    Damien Philippon

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  1. Patrick Taillandier
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  2. Benoit Gaudou
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  4. Quang-Nghi Huynh
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Appendix

Appendix

GAMA, which is under a GNU General Public License, can be downloaded from the GAMA Website: http://www.gama-platform.org. It is available in 32 and 64 bits for Windows, OS-X and Linux. GAMA requires a Java Virtual Machine (1.8) to run, but the website proposes a version of GAMA with an embedded JVM. A library of more than 300 models is provided with GAMA: this library contains models presenting how to use the different features of GAMA (data importation, agent movement, 3D display, etc.), classic toy models (ant foraging, boids, Schelling, SugarScape…) and tutorials. The Website of GAMA provides a complete documentation on the platform. It provides as well a series of tutorials to learn the bases of GAML. At last, an online user groupFootnote 2 is available to ask questions about the platform.

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Taillandier, P., Gaudou, B., Grignard, A. et al. Building, composing and experimenting complex spatial models with the GAMA platform. Geoinformatica 23, 299–322 (2019). https://doi.org/10.1007/s10707-018-00339-6

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