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International Conference on Principles and Practice of Multi-Agent Systems

PRIMA 2013: PRIMA 2013: Principles and Practice of Multi-Agent Systems pp 117–131Cite as

GAMA 1.6: Advancing the Art of Complex Agent-Based Modeling and Simulation

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNAI,volume 8291)

Abstract

Agent-based models tend to be more and more complex. In order to cope with this increase of complexity, powerful modeling and simulation tools are required. These last years have seen the development of several platforms dedicated to the development of agent-based models. While some of them are still limited to the development of simple models, others allow to develop rich and complex models. Among them, the GAMA modeling and simulation platform is aimed at supporting the design of spatialized, multiple-paradigms and multiple-scales models. Several papers have already introduced GAMA, notably in earlier PRIMA conferences, and we would like, in this paper, to introduce the new features provided by GAMA 1.6, the latest revision to date of the platform. In particular, we present its capabilities concerning the tight combination of 3D visualization, GIS data management, and multi-level modeling. In addition, we present some examples of real projects that rely on GAMA to develop complex models.

Keywords

  • Agent-based modeling
  • simulation
  • GIS
  • multi-level
  • ODE
  • platform
  • visualization
  • complex systems

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References

  1. Apolloni, A., Poletto, C., Colizza, V., et al.: Age-specific contacts and travel patterns in the spatial spread of 2009 h1n1 influenza pandemic. BMC Infectious Diseases 13(1), 1–18 (2013)

    CrossRef  Google Scholar 

  2. Araujo, F., Valente, J., Al-Zinati, M., Kuiper, D., Zalila-Wenkstern, R.: Divas 4.0: A framework for the development of situated multi-agent based simulation systems. In: Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems, AAMAS 2013, pp. 1351–1352. International Foundation for Autonomous Agents and Multiagent Systems (2013)

    Google Scholar 

  3. Axelrod, R.M.: The complexity of cooperation: Agent-based models of competition and collaboration. Princeton University Press (1997)

    Google Scholar 

  4. Banos, A., Marilleau, N.: Improving individual accessibility to the city: An agent-based modelling approach. In: ECCS (2012)

    Google Scholar 

  5. Colizza, V., Vespignani, A.: Epidemic modeling in metapopulation systems with heterogeneous coupling pattern: Theory and simulations. Journal of Theoretical Biology 251(3), 450–467 (2008)

    MathSciNet  CrossRef  Google Scholar 

  6. Crooks, A.T., Castle, C.J.E.: Agent-Based Models of Geographical Systems. Springer Netherlands, Dordrecht (2012)

    Google Scholar 

  7. Daniel Kornhauser, U.W., Rand, W.: Design Guidelines for Agent Based Model Visualization. Journal of Artificial Societies and Social Simulation 12(2) (2009)

    Google Scholar 

  8. De Wolf, T., Holvoet, T.: Emergence versus self-organisation: Different concepts but promising when combined. In: Brueckner, S.A., Di Marzo Serugendo, G., Karageorgos, A., Nagpal, R. (eds.) ESOA 2005. LNCS (LNAI), vol. 3464, pp. 1–15. Springer, Heidelberg (2005)

    CrossRef  Google Scholar 

  9. Drogoul, A., Amouroux, E., Caillou, P., Gaudou, B., Grignard, A., Marilleau, N., Taillandier, P., Vavasseur, M., Vo, D.A., Zucker, J.D.: Gama: multi-level and complex environment for agent-based models and simulations. In: AAMAS 2013, pp. 1361–1362. International Foundation for Autonomous Agents and Multiagent Systems (2013)

    Google Scholar 

  10. Edmonds, B., Moss, S.: From KISS to KIDS – an ‘Anti-simplistic’ modelling approach. In: Davidsson, P., Logan, B., Takadama, K. (eds.) MABS 2004. LNCS (LNAI), vol. 3415, pp. 130–144. Springer, Heidelberg (2005)

    CrossRef  Google Scholar 

  11. Gaudou, B., Sibertin-Blanc, C., Thérond, O., Amblard, F., Arcangeli, J.P., Balestrat, M., Charron-Moirez, M.H., Gondet, E., Hong, Y., Louail, T., Mayor, E., Panzoli, D., Sauvage, S., Sanchez-Perez, J., Taillandier, P., Nguyen, V.B., Vavasseur, M., Mazzega, P.: The MAELIA multi-agent platform for integrated assessment of low-water management issues (regular paper). In: International Workshop on Multi-Agent-Based Simulation (MABS), Saint-Paul, MN, USA. Springer (2013)

    Google Scholar 

  12. Gil-Quijano, J., Louail, T., Hutzler, G.: From biological to urban cells: lessons from three multilevel agent-based models. In: Desai, N., Liu, A., Winikoff, M. (eds.) PRIMA 2010. LNCS, vol. 7057, pp. 620–635. Springer, Heidelberg (2012)

    CrossRef  Google Scholar 

  13. Grignard, A., Drogoul, A., Zucker, J.D.: A model-view/controller approach to support visualization and online data analysis of agent-based simulation. In: Proceedings of 2013 IEEE RIVF (2013)

    Google Scholar 

  14. Grignard, A., Drogoul, A., Zucker, J.-D.: Online analysis and visualization of agent based models. In: Murgante, B., Misra, S., Carlini, M., Torre, C.M., Nguyen, H.-Q., Taniar, D., Apduhan, B.O., Gervasi, O. (eds.) ICCSA 2013, Part I. LNCS, vol. 7971, pp. 662–672. Springer, Heidelberg (2013)

    CrossRef  Google Scholar 

  15. Hanski, I.: Metapopulation Ecology. Oxford University Press (1999)

    Google Scholar 

  16. Kermack, W.O., McKendrick, A.G.: A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London 115(772), 700–721 (1927)

    CrossRef  MATH  Google Scholar 

  17. Lamarche-Perrin, R., Demazeau, Y., Vincent, J.-M.: How to Build the Best Macroscopic Description of your Multi-agent System? In: Demazeau, Y., Ishida, T., Corchado, J.M., Bajo, J. (eds.) PAAMS 2013. LNCS, vol. 7879, pp. 157–169. Springer, Heidelberg (2013)

    CrossRef  Google Scholar 

  18. Le Page, C., Bousquet, F., Bakam, I., Bah, A., Baron, C.: Cormas: A multiagent simulation toolkit to model natural and social dynamics at multiple scales. In: Proceedings of Workshop “The Ecology of Scales”, Wageningen, The Netherlands (2000)

    Google Scholar 

  19. Lotka, A.J.: Contribution to the theory of periodic reactions. The Journal of Physical Chemistry 14(3), 271–274 (1909)

    CrossRef  Google Scholar 

  20. Luke, S., Cioffi-Revilla, C., Panait, L., Sullivan, K., Balan, G.: Mason: A multiagent simulation environment. Simulation 81(7), 517–527 (2005)

    CrossRef  Google Scholar 

  21. Morvan, G.: Multi-level agent-based modeling-bibliography. arXiv preprint arXiv:1205.0561 (2013)

    Google Scholar 

  22. Nguyen, T.N.A., Zucker, J.D., Nguyen, H.D., Drogoul, A., Vo, D.A.: A hybrid macro-micro pedestrians evacuation model to speed up simulation in road networks. In: Dechesne, F., Hattori, H., ter Mors, A., Such, J.M., Weyns, D., Dignum, F. (eds.) AAMAS 2011 Workshops. LNCS, vol. 7068, pp. 371–383. Springer, Heidelberg (2012)

    CrossRef  Google Scholar 

  23. North, M.J., Collier, N.T., Ozik, J., Tatara, E.R., Macal, C.M., Bragen, M., Sydelko, P.: Complex adaptive systems modeling with repast simphony. Complex Adaptive Systems Modeling 1(1), 1–26 (2013)

    CrossRef  Google Scholar 

  24. Railsback, S.F., Lytinen, S.L., Jackson, S.K.: Agent-based Simulation Platforms: Review and Development Recommendations. Simulation, 609–623 (2006)

    Google Scholar 

  25. Servat, D., Perrier, E., Treuil, J.-P., Drogoul, A.: When agents emerge from agents: Introducing multi-scale viewpoints in multi-agent simulations. In: Sichman, J.S., Conte, R., Gilbert, N. (eds.) MABS 1998. LNCS (LNAI), vol. 1534, pp. 183–198. Springer, Heidelberg (1998)

    CrossRef  Google Scholar 

  26. Taillandier, P., Vo, D.-A., Amouroux, E., Drogoul, A.: GAMA: A simulation platform that integrates geographical information data, agent-based modeling and multi-scale control. In: Desai, N., Liu, A., Winikoff, M. (eds.) PRIMA 2010. LNCS, vol. 7057, pp. 242–258. Springer, Heidelberg (2012)

    CrossRef  Google Scholar 

  27. Taillandier, P., Thérond, O., Gaudou, B.: A new BDI agent architecture based on the belief theory. Application to the modelling of cropping plan decision-making (regular paper). In: International Environmental Modelling and Software Society (iEMSs), Leipzig, Germany, July 1-5 (2012)

    Google Scholar 

  28. Tisue, S., Wilensky, U.: Netlogo: A simple environment for modeling complexity. In: International Conference on Complex Systems, pp. 16–21 (2004)

    Google Scholar 

  29. Treuil, J.P., Drogoul, A., Zucker, J.D.: Modélisation et simulation à base d’agents: exemples commentés, outils informatiques et questions théoriques. Dunod (2008)

    Google Scholar 

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Author information

Authors and Affiliations

  1. UMI 209 UMMISCO/MSI, UPMC, France

    Arnaud Grignard

  2. UMI 209 UMMISCO/MSI, IRD, Vietnam

    Duc An Vo & Alexis Drogoul

  3. UMR 6266 IDEES, CNRS/University of Rouen, France

    Patrick Taillandier

  4. UMR 5505 IRIT, CNRS/University of Toulouse, France

    Benoit Gaudou

  5. DREAM-CTU/IRD, CICT, Can Tho University, Vietnam

    Nghi Quang Huynh

Authors
  1. Arnaud Grignard
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  2. Patrick Taillandier
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  3. Benoit Gaudou
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  4. Duc An Vo
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  5. Nghi Quang Huynh
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  6. Alexis Drogoul
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Editor information

Editors and Affiliations

  1. Dipartimento di Informatica,, Università degli Studi di Torino, via Pessinetto 12,, 10149, Torino, Italy

    Guido Boella

  2. Division of Mathematical Sciences, Nanyang Technological University, Singapore

    Edith Elkind

  3. Department of Information Science, University of Otago, Dunedin, New Zealand

    Bastin Tony Roy Savarimuthu & Martin K. Purvis & 

  4. Department of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands

    Frank Dignum

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Grignard, A., Taillandier, P., Gaudou, B., Vo, D.A., Huynh, N.Q., Drogoul, A. (2013). GAMA 1.6: Advancing the Art of Complex Agent-Based Modeling and Simulation. In: Boella, G., Elkind, E., Savarimuthu, B.T.R., Dignum, F., Purvis, M.K. (eds) PRIMA 2013: Principles and Practice of Multi-Agent Systems. PRIMA 2013. Lecture Notes in Computer Science(), vol 8291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-44927-7_9

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  • DOI: https://doi.org/10.1007/978-3-642-44927-7_9

  • Publisher Name: Springer, Berlin, Heidelberg

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