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PAMS – A New Collaborative Framework for Agent-Based Simulation of Complex Systems

  • Trong Khanh Nguyen
  • Nicolas Marilleau
  • Tuong Vinh Ho
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5357)

Abstract

Major researches in the domain of complex systems are interdisciplinary, collaborative and geographically distributed. The purpose of our work is to explore a new collaborative approach that facilitates scientist’s interactions during the modelling and simulating process. The originality of the presented approach is to consider models and simulators as a board of the collaboration: a shared object manipulated by a group of scientists. Agent-based simulations are powerful tools for studying complex systems. In this context, we develop a collaborative platform dedicated to agent-based simulation (PAMS). This new environment integrates common collaborative tools (e.g. videoconferencing, instant messaging, whiteboard) and specific tools to share and manipulate models, simulators, experiments and results... The current version of PAMS is based technologies coming from distributed systems. Today PAMS has been designed to support major agent based simulation frameworks. This paper aims to give an overview of the PAMS environment by defining the collaborating approach, the framework architecture and an example of its utilization.

Keywords

Collaborative simulation agent-based simulation distributed systems 

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References

  1. 1.
    Severance, C., Hardin, J., Golden, G., Crouchley, R., Fish, A., Finholt, T., Kirschner, B., Eng, J., Allan, R.: Using the Sakai collaborative toolkit in e-Research applications. Concurrency and Computation: Practice and Experience 19(12), 1643–1652 (2007)CrossRefGoogle Scholar
  2. 2.
    Saint-Voirin, D.: Contribution à la modélisation et à l’analyse des systèmes coopératif: application à la e-maintenance. Université de Franche-Comté, Besançon (2006)Google Scholar
  3. 3.
    Amouroux, E., Quang, C.T., Boucher, A., Drogoul, A.: GAMA: an environment for implementing and running spatially explicit multi-agent simulations. In: Prima-2007, Bangkok (2007)Google Scholar
  4. 4.
    Conway, J.: The Game of Life. Scientific American 223, 120–123 (1970)CrossRefGoogle Scholar
  5. 5.
    Henriksen, J.O., Lorenz, P., Hanisch, A., Osterburg, S., Schriber, T.J.: Web based simulation center: professional support for simulation projects. Winter Simulation Conference-2002 1, 807–815 (2002)CrossRefGoogle Scholar
  6. 6.
    Ahmed, K., Brahim, B.: Towards a Web Based Simulation Groupware: Experiment with BSCW. Information Technology Journal 1812(5638), 332–337 (2008)Google Scholar
  7. 7.
    Terna, P.: Simulation Tools for Social Scientists: Building Agent Based Models with SWARM. Journal of Artificial Societies and Social Simulation 1(2) (1998)Google Scholar
  8. 8.
    North, M.J., Collier, N.T., Vos, J.R.: Experiences Creating Three Implementations of the Repast Agent Modeling Toolkit. ACM Transactions on Modeling and Computer Simulation 16(1), 1–25 (2006)CrossRefGoogle Scholar
  9. 9.
    Wilensky, U., Evanston, I.L.: NetLogo. Center for Connected Learning and Computer Based Modeling, Northwestern University (1999)Google Scholar
  10. 10.
    Railsback, S.F.: Agent-based based Models in Ecology: Patterns and Alternative Theories of Adaptive Behaviour. In: Agent-Based Computational Modelling, pp. 139–152. Physica-Verlag (2006)Google Scholar
  11. 11.
    Horstmann, T., Bentley, R.: Distributed authoring on the Web with the BSCW shared workspace system. StandardView 5(1), 9–16 (1997)CrossRefGoogle Scholar
  12. 12.
    Becker, R., Becker, B., Knotte, M., KreiBlemeyer, I.: Manual eGroupware 1.4. Creative Commons (2007)Google Scholar
  13. 13.
    Yang, X., Allan, R.: Web-Based Virtual Research Environments (VRE): Support Collaboration in e-Science. In: WI-IATW 2006: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology, pp. 184–187. IEEE Computer Society, Los Alamitos (2006)Google Scholar
  14. 14.
    Severance, C., Hardin, J., Golden, G., Crouchley, R., Fish, A., Finholt, T., Kirschner, B., Eng, J., Allan, R.: Using the Sakai collaborative toolkit in e-Research applications. Concurrency and Computation: Practice and Experience 19(12), 1643–1652 (2007)CrossRefGoogle Scholar
  15. 15.
    Reenskaug, T.: The Model-View-Controller (MVC) Its Past and Present. JavaZONE Conference, Oslo (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Trong Khanh Nguyen
    • 2
  • Nicolas Marilleau
    • 1
  • Tuong Vinh Ho
    • 2
  1. 1.Geodes, Institut de Recherche pour le développment (IRD)Bondy CedexFrance
  2. 2.MSI LabInstitut de la Francophonie pour l’Informatique(IFI)Ha NoiViet Nam

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