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Agent-Oriented Modeling and Agent-Based Simulation

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Conceptual Modeling for Novel Application Domains (ER 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2814))

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Abstract

Agent-oriented modeling of software and information systems and agent-based simulation are commonly viewed as two separate fields with different concepts and techniques. We argue that a sufficiently expressive agent-oriented modeling language for information systems analysis and design should – with some minor extensions – also be usable for specifying simulation models that can be executed by an agent-based simulation system. Specifically, we investigate the suitability of the Agent-Object-Relationship modeling language (AORML) proposed in [Wag03] for simulation. We show that the AOR meta-model and the meta-model of discrete event simulation can be combined into a model of agent-based discrete event simulation in a natural way.

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References

  1. Booth, G.: CourseWare Programmer’s Guide, Yale Institute for Biospheric Studies (1999)

    Google Scholar 

  2. 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 

  3. Conte, R., Dignum, F.: From Social Monitoring to Normative Influence. Journal of Artificial Societies and Social Simulation 4(2) (2001)

    Google Scholar 

  4. Davidsson, P.: Agent Based Social Simulation: A Computer Science View. Journal of Artificial Societies and Social Simulation 5(1) (2002), http://jasss.soc.surrey.ac.uk/5/1/7.html

  5. Davies, A.: EcoSim: An Interactive Simulation, Duquesne Universität, Pittsburgh (2002)

    Google Scholar 

  6. Dennett, D.C.: Intentional Systems. The Journal of Philosophy 68 (1971)

    Google Scholar 

  7. Edmonds, B., Wallis, S.: Towards an Ideal Social Simulation Language, Manchester Metropolitan University (2002)

    Google Scholar 

  8. Ferber, J., Gutknecht, O.: A meta-model for the analysis and design of organizations in multi-agent systems. In: Proceedings of the Third International Conference on Multi-Agent Systems (ICMAS 1998), pp. 128–135. IEEE Computer Society Press, Los Alamitos (1998)

    Google Scholar 

  9. Hales, D.: Evolving Specialisation, Altruism and Group-Level Optimisation Using Tags. In: Sichman, J.S., Bousquet, F., Davidsson, P. (eds.) MABS 2002. LNCS (LNAI), vol. 2581, pp. 26–35. Springer, Heidelberg (2003)

    Google Scholar 

  10. Defense Modelling and Simulation Office: High Level Architecture (2002)

    Google Scholar 

  11. Jacobson, I.: The Object Advantage. Addison-Wesley, Workingham (1994)

    Google Scholar 

  12. Klügl, F.: Multiagentensimulation. Addison-Wesley, Reading (2001)

    Google Scholar 

  13. Labarthe, O., Tranvouez, E., Ferrarini, A., Espinasse, B.: A Heterogeneous Multi-Agent Modeling for Distributed Simulation of Supply Chains. In: Mařík, V., McFarlane, D.C., Valckenaers, P. (eds.) HoloMAS 2003. LNCS (LNAI), vol. 2744, pp. 134–145. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  14. Ferber, J., Gutknecht, O., Michel, F.: MadKit Development Guide (2002)

    Google Scholar 

  15. Minar, N., Burkhart, R., Langton, C., Askenazi, M.: The Swarm Simulation System: A Toolkit For Building Multi-Agent Simulations (1996)

    Google Scholar 

  16. Moss, S., Gaylard, H., Wallis, S., Edmonds, B.: SDML: A Multi- Agent Language for Organizational Modelling. Computational and Mathematical Organization Theory 4(1), 43–70 (1998)

    Article  Google Scholar 

  17. Noda, I., Matsubara, H., Hiraki, K., Frank, I.: Soccer Server: a tool for research on multiagent systems. Applied Artificial Intelligence 12(2-3) (1998)

    Google Scholar 

  18. SICS: Trading Agent Competition (2002), See http://www.sics.se/tac/

  19. Wagner, G.: The Agent-Object-Relationship Meta-Model: Towards a Unified View of State and Behavior. Information Systems 28(5), 475–504 (2003)

    Article  MATH  Google Scholar 

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Wagner, G., Tulba, F. (2003). Agent-Oriented Modeling and Agent-Based Simulation. In: Jeusfeld, M.A., Pastor, Ó. (eds) Conceptual Modeling for Novel Application Domains. ER 2003. Lecture Notes in Computer Science, vol 2814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39597-3_20

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  • DOI: https://doi.org/10.1007/978-3-540-39597-3_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20257-8

  • Online ISBN: 978-3-540-39597-3

  • eBook Packages: Springer Book Archive

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