Skip to main content

Part of the book series: Interdisciplinary Studies in Economics and Management ((ISEM,volume 5))

  • 383 Accesses

7 Summary

In this work we introduced SIMENV, a generic simulation framework suitable for agent-based simulations featuring the support of heterogeneous agents, hierarchical scheduling, and flexible specification of design parameters. One key aspect of this framework is the design specification: we use a format based on the Extensible Markup Language (XML), that is simple-structured yet still enables the design of flexible models, with the possibility of varying both agent population and parameterization. Further, the tool allows the definition of communication channels to single or group of agents, and handles the information exchange. Also, both (groups of) agents and communications channels can be added and removed at runtime by the agents, thus allowing dynamic settings with a agent population and/or communication structures varying during the simulation time. A further issue in agent-based simulations, especially when ready-made components are used, is the heterogeneity arising from both the agents’ implementations and the underlying platforms: for this, we presented a wrapper technique for mapping the functionality of agents living in an interpreter-based environment to a standardized JAVA interface, thus facilitating the task for any control mechanism (like a simulation manager) because it has to handle only one set of commands for all agents involved. Again, this mapping is made by an XML-based definition format.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  • Dey, A. and Mukerjee, R. (1999). Fractional Factorial Plans. Wiley, New York.

    Google Scholar 

  • Eaton, J. W. (2003). Octave software version 2.0.17,

    Google Scholar 

  • Gosling, J., Joy, B., Steele, G. L., and Bracha, G. (2000). The Java Language Specification. Addison-Wesley, Boston, second edition.

    Google Scholar 

  • Meyer, D., Buchta, C., Karatzoglou, A., Leisch, F., and Hornik, K. (2003). A simulation framework for heterogeneous agents. Computational Economics, 22(2):285–301.

    Article  Google Scholar 

  • Meyer, D., Karatzoglou, A., Buchta, C., Leisch, F., and Hornik, K. (2001). Running agent-based simulations. Working Paper 80, SFB “Adaptive Information Systems and Modeling in Economics and Management Science”.

    Google Scholar 

  • Meyer, D., Leisch, F., Hothorn, T., and Hornik, K. (2004). StatDataML: An XML format for statistical data. Computational Statistics, 19(3):493–509.

    Google Scholar 

  • R Development Core Team (2003). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-00-3.

    Google Scholar 

  • Richter, H. and Möarz, L. (2000). Towards a standard process: The use of UML for designing simulation models. In Proceedings of the 2000 Winter Simulation Conference, pages 394–398.

    Google Scholar 

  • The Mathworks, Inc. (2003). MATLAB software: Release 13. Natick, MA: The Mathworks, Inc.,

    Google Scholar 

  • Wilson, L. F., Burroughs, D., Sucharitaves, J., and Kumar, A. (2000). An agent-based framework for linking distributed simulations. In Proceedings of the 2000 Winter Simulation Conference, pages 1713–1721.

    Google Scholar 

  • World Wide Web Consortium (2000). Extensible Markup Language (XML), 1.0 (2nd Edition). Recommendation 6-October-2000. Edited by Tim Bray (Textuality and Netscape), Jean Paoli (Microsoft), C. M. Sperberg-McQueen (University of Illinois at Chicago and Text Encoding Initiative), and Eve Maler (Sun Microsystems, Inc.). Reference:

    Google Scholar 

Download references

Author information

Authors and Affiliations


Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag/Wien

About this chapter

Cite this chapter

Meyer, D., Karatzoglou, A. (2005). The Artificial Economy: A Generic Simulation Environment for Heterogeneous Agents. In: Taudes, A. (eds) Adaptive Information Systems and Modelling in Economics and Management Science. Interdisciplinary Studies in Economics and Management, vol 5. Springer, Vienna.

Download citation

  • DOI:

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-20684-3

  • Online ISBN: 978-3-211-29901-2

  • eBook Packages: Business and Economics

Publish with us

Policies and ethics