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Gama Platform

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GAMA Platform
GAMA Platform logo
GAMA Platform IDE Screenshot
Screenshot from the GAMA Platform 1.8.0
Developer(s)IRD
Initial releaseOctober 2009; 14 years ago (2009-10)....[1]
Stable release
1.8.1 / June 23, 2020; 3 years ago (2020-06-23)[2]
Repositoryhttps://github.com/gama-platform/gama
Written inJava
Engine
    Operating systemWindows, macOS, Linux
    Platformx86-64
    Size100 ~ 275 MB
    Available inEnglish
    LicenseGPL3
    Websitehttp://gama-platform.org

    Search Gama Platform on Amazon.

    GAMA[3][4] (GIS Agent-based Modeling Architecture) is a simulation platform with a complete modelling and simulation integrated development environment (IDE) for building spatially explicit agent-based simulations.[5][6]

    About[edit]

    The GAMA Platform is agent-based modeling software that was originally (2007-2010) developed by the Vietnamese-French research team MSI (located at IFI, Hanoi, and part of the IRD - SU International Research Unit UMMISCO). It is now developed by an international consortium of academic and industrial partners led by UMMISCO, including INRAE, the University of Toulouse 1, the University of Rouen, the University of Orsay, the University of Can Tho, Vietnam, the National University of Hanoi, EDF R&D, CEA LISC, and MIT Media Lab.[6]

    GAMA was designed to allow domain experts without a programming background to model phenomena from their field of expertise[7].

    The GAMA environment enables exploration of emergent phenomena. It comes with a models library including examples from several domains, such as economics, biology, physics, chemistry, psychology, and system dynamics[8]. The GAMA simulation panel allows exploration by modifying switches, sliders, choosers, inputs, and other user interface elements that the modeler chooses to make available.[9]

    Technical foundation[edit]

    GAMA Platform is free and open-source software, released under a GNU General Public License (GPL3)[10]. It is written in Java and runs on the Java virtual machine (JVM)[11]. All core components and extensions are written in Java, but end users do not need to work in Java at all if they use a published build of the platform; instead, they would write all models using GAML (described below).

    Multiple application domains[edit]

    GAMA was developed with a very general approach and can be used for many application domains[5]. GAMA is mostly present in applications domains like transport[12][13][14][15][16], urban planning[14][15][16], disaster response[17], epidemiology[18][19][20], analysis of multirobot systems[21][22], and the environment[14][15][16], with special emphasis on analyses that use GIS data[23][24]

    High-level Agent-based language[edit]

    GAML (GAma Modeling Language) is the dedicated language used in GAMA. It is an agent-based language, that provides the possibility to build a model with several paradigms of modeling.[5]

    This high-level language was inspired by Smalltalk and Java, GAMA has been developed to be used by non-computer scientists.[5]

    User interface[edit]

    Modelers may use many visual representations for the same model, in order to highlight a certain aspect of a simulation. These include 2D/3D displays, with basic control of lighting, textures, and cameras. Standard charts such as series plots may also be constructed.[5]

    Project examples[edit]

    The developers maintain a community-sourced list of scientific projects that use GAMA[25].

    Some of the larger efforts include:

    • Hoan Kiem Air[14]: Agent based modeling and simulation of the urban management on traffic and air pollution through tangible interface.
    • Proxymix[26]: Visualization tool about the influence of spatial configuration on human collaboration.
    • CityScope Champs-Elysées[15]: An interactive platform to improve decision-making related to the revitalization of the Champs Élysées.
    • ESCAPE[16]: A Multi-modal Urban Traffic Agent-Based Framework to Study Individual Response to Catastrophic Events.
    • COMOKIT[19][20]: Generic model of public policies to contain the spread of COVID-19 epidemics in a city, validated on the basis of different case studies.

    Users[edit]

    Several academic institutions teach modeling and simulation courses based on GAMA. It is taught in the Urban Simulation class at the Potsdam University of Applied Sciences[27], and at the University of Salzburg[28]. It is also used and taught annually at the Multi-platform International Summer School on Agent-Based Modelling & Simulation[29].

    See also[edit]

    References[edit]

    1. "GAMA 1.1". GAMA Documentation.
    2. Github https://github.com/gama-platform/gama/releases/tag/v1.8.1. Missing or empty |title= (help)
    3. Taillandier, Patrick; Gaudou, Benoit; Grignard, Arnaud; Huynh, Quang-Nghi; Marilleau, Nicolas; Caillou, Philippe; Philippon, Damien; Drogoul, Alexis (April 2019). "Building, composing and experimenting complex spatial models with the GAMA platform" (PDF). GeoInformatica. Springer US. 23 (2): 299–322. doi:10.1007/s10707-018-00339-6. ISSN 1573-7624. Unknown parameter |s2cid= ignored (help)
    4. Grignard, Arnaud; Taillandier, Patrick; Gaudou, Benoit; Vo, Duc An; Huynh, Quand-Nghi; Drogoul, Alexis (2013). "GAMA 1.6: Advancing the art of complex agent-based modeling and simulation" (PDF). International Conference on Principles and Practice of Multi-Agent Systems. Lecture Notes in Computer Science. Springer. 8291: 117–131. doi:10.1007/978-3-642-44927-7_9. ISBN 978-3-642-44926-0.
    5. 5.0 5.1 5.2 5.3 5.4 "GAMA · GAMA-Platform". gama-platform.github.io. Retrieved 1 November 2019. Material was copied from this source, which is available under a Creative Commons Attribution 4.0 International License.
    6. 6.0 6.1 "Introduction · GAMA-Platform". gama-platform.github.io. Retrieved 1 November 2019. Material was copied from this source, which is available under a Creative Commons Attribution 4.0 International License.
    7. Taillandier, Patrick; Gaudou, Benoit; Grignard, Arnaud; Huynh, Quang-Nghi; Marilleau, Nicolas; Caillou, Philippe; Philippon, Damien; Drogoul, Alexis (December 23, 2018), "Building, Composing and Experimenting Complex Spatial Models with the GAMA Platform" (PDF), GeoInformatica, 23 (2): 299–322, doi:10.1007/s10707-018-00339-6 Unknown parameter |s2cid= ignored (help)
    8. "Tutorials". GAMA-Platform. Retrieved 2019-10-30.
    9. "Controls of experiments". GAMA-Platform. Retrieved 2019-10-30.
    10. "gama/LICENSE at master - gama-platform/gama". Github. 29 April 2020.
    11. "Architecture of GAMA". GAMA-Platform.
    12. Kaziyeva, Dana; Wallentin, Gudrun; Loidl, Martin; Mohr, Stefan; Neuwirth, Christian (2018). "Reviewing Software for Agent-based Bicycle Flow Models". GI Forum. 6.
    13. Hutzler, Guillaume; Klaudel, Hanna; Sali, Abderrahmane (2020). "Filtering Distributed Information to Build a Plausible Scene for Autonomous and Connected Vehicles". 17th International Conference on Distributed Computing and Artificial Intelligence.
    14. 14.0 14.1 14.2 14.3 "WARMTeam/HoanKiemAir". Github. Hanoi, Vietnam: WARM Team. Retrieved 2019-10-30.
    15. 15.0 15.1 15.2 15.3 "CityScope Champs_Elysées: An interactive platform to improve decision-making related to the revitalization of the Champs Élysées". MIT Media Lab. MIT. Retrieved 2020-03-30.
    16. 16.0 16.1 16.2 16.3 Chapuis, Kevin; Taillandier, Patrick; Gaudou, Benoit; Drogoul, Alexis; Daudé, Eric (2018), A Multi-modal Urban Traffic Agent-Based Framework to Study Individual Response to Catastrophic Events (PDF), Springer, Cham (published 24 October 2018), doi:10.1007/978-3-030-03098-8_28, ISBN 978-3-030-03097-1
    17. Alonso Vicario, S; Mazzoleni, M; Bhamidipati, S; Gharesifard, M; Ridolfi, E; Pandolfo, C; Alfonso, L (2020). "Unraveling the influence of human behaviour on reducing casualties during flood evacuation". Hydrological Sciences Journal: 1–17. doi:10.1080/02626667.2020.1810254.
    18. Jindal, Akshay (2017). "Agent-Based Modeling and Simulation of Mosquito-Borne Disease Transmission". Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017).
    19. 19.0 19.1 "CoViD19". gama-platform.github.io. GAMA Team. Retrieved 2020-02-15.
    20. 20.0 20.1 "COMOKIT". github.com. Hanoi, Vietnam: COMOKIT Team. Retrieved 2020-02-15.
    21. Humann, James; Spero, Eric (2018). "Modeling and simulation of multi-UAV, multi-operator surveillance systems". 2018 Annual IEEE International Systems Conference (SysCon): 1–8. doi:10.1109/SYSCON.2018.8369546. ISBN 978-1-5386-3664-0. Unknown parameter |s2cid= ignored (help)
    22. Humann, James; Pollard, Kimberly (2019). "Human Factors in the Scalability of Multirobot Operation: A Review and Simulation". 2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC): 700–707. doi:10.1109/SMC.2019.8913876. ISBN 978-1-7281-4569-3. Unknown parameter |s2cid= ignored (help)
    23. Thierry, Hugo; Rogers, Haldre (2020). "Where to rewild? A conceptual framework to spatially optimize ecological function". Proceedings of the Royal Society B. 287 (1922). doi:10.1098/rspb.2019.3017. PMC 7126074 Check |pmc= value (help). PMID 32126955 Check |pmid= value (help).
    24. Abar, Sameera; Theodoropoulos, Georgios K; Lemarinier, Pierre; O'Hare, Gregory (2017). "Agent Based Modelling and Simulation tools: A review of the state-of-art software". Computer Science Review. 24: 13–33. doi:10.1016/j.cosrev.2017.03.001.
    25. "GAMA-platform References". gama-platform.github.io. Retrieved 18 August 2020.
    26. "Proxymix: Influence of spatial configuration on human collaboration". MIT Media Lab. MIT. Retrieved 2019-10-30.
    27. Szczepanska, Timo; Priebe, Max; Schroder, Tobias (2020). Teaching the Complexity of Urban Systems with Participatory Social Simulation. Springer. Search this book on
    28. "UNIGIS Summer School Spatial Simulation Modelling".
    29. "Multi-platform International Summer School on Agent-Based Modelling & Simulation for Renewable Resources Management".



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