Abstract
In this paper, we introduce the GAMA (Gis & Agent-based Modelling Architecture) simulation platform, which aims at providing field experts, modellers, and computer scientists with a complete modelling and simulation development environment for building spatially explicit multi-agent simulations.
The most important requirements of spatially explicit multi-agent simulations that our platform fulfils are: (1) the ability to transparently use complex Geographical Information System (GIS) data as an environment for the agents; (2) the ability to handle a vast number of (heterogeneous) agents (3); the ability to offer a platform for automated controlled experiments (by automatically varying parameters, recording statistics, etc.); (4) the possibility to let non-computer scientists design models and interact with the agents during simulations.
While still in its implementation phase, the platform is currently used for two main applications. One is about the modelling of the spread of avian influenza in a province of North Vietnam in collaboration with CIRAD (French Agricultural Research Centre working for International Development). Its goal is to simulate the poultry value chain of a whole province using geolocalised data, and to use this to optimise a monitoring network. A second application conducted with the Institute for Marine Geology and Geophysics (VAST, Hanoi) is about using an interactive simulation for supporting decision-making during urban post-disaster situations. This application relies on geolocalised data as well, and requires facilities of interaction between users and the simulation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Railsback, S.F., Lytinen, S.L., Jackson, S.K.: Agent-based Simulation Platforms: Review and Development Recommendations. SIMULATION 82(9), 609–623 (2006)
Weyns, D., Van Dyke Parunak, H., Michel, F., Holvoet, T., Ferber, J.: Environments for Multiagent Systems, State-of-the-Art and Research Challenges. LNAI, vol. 3477. Springer, Heidelberg (2005)
Minar, N., Burkhart, R., Langton, C., Askenazi, M.: The Swarm simulation system: A toolkit for building multi-agent simulations. Santa Fe Institute working paper (1996)
Tissue, S., Wilensky, U.: Netlogo: A Simple Environment for Modelling Complexity. In: International Conference on Complex Systems (2004)
Ferber, J.: Multi-Agent Systems, An Introduction to Distributed Artificial Intelligence. Addison-Wesley, Reading (1999)
Drogoul, A., Ferber, J.: Multi-Agent Simulation as a Tool for Modelling Societies: Application to Social Differentiation in Ant Colonies. In: Castelfranchi, C., Werner, E. (eds.) Artificial Social Systems, Berlin, vol. 830, pp. 3–23. Springer, Heidelberg (1994)
Desvaux, S., et al.: HPAI Surveillance Programme in Cambodia: Results and Perspectives. In: OIE/FAO international Conference on Avian Influenza. Developments in Biologicals, vol. 124, pp. 211–224 (2005)
Nguyen-Hung, P.: Decision support systems applied to earthquake and tsunami risk assessment and loss mitigation. Colloque international sur les Application de la télédétection, des SIG et des GPS pour la réduction des risques naturels et le développement durable (2006)
Kitano, H.: RoboCup Rescue: A Grand Challenge for Multi-Agent Systems. In: International Conference on Multi-Agent Systems, pp. 5–12 (2000)
Sempé, F., Nguyen-Duc, M., Boissau, S., Boucher, A., Drogoul, A.: An artificial maieutic approach for eliciting experts’ knowledge in multi-agent simulations. In: Sichman, J.S., Antunes, L. (eds.) MABS 2005. LNCS, vol. 3891, pp. 75–87. Springer, Heidelberg (2006)
Castella, J.C., Boissau, S., Tran-Ngoc, T., Dang-Dinh, Q.: Agrarian transition and lowland-upland interactions in mountain areas in northern Vietnam: Application of a multi-agent simulation model. Agricultural Systems 86(3), 312–332 (1986)
Bousquet, F., Bakam, I., Proton, H., Le Page, C.: Cormas: common-pool resources and multi-agent Systems. In: Mira, J., Moonis, A., de Pobil, A.P. (eds.) IEA/AIE 1998. LNCS (LNAI), vol. 1416, pp. 826–837. Springer, Heidelberg (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Amouroux, E., Chu, TQ., Boucher, A., Drogoul, A. (2009). GAMA: An Environment for Implementing and Running Spatially Explicit Multi-agent Simulations. In: Ghose, A., Governatori, G., Sadananda, R. (eds) Agent Computing and Multi-Agent Systems. PRIMA 2007. Lecture Notes in Computer Science(), vol 5044. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01639-4_32
Download citation
DOI: https://doi.org/10.1007/978-3-642-01639-4_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01638-7
Online ISBN: 978-3-642-01639-4
eBook Packages: Computer ScienceComputer Science (R0)