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

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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.

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© 2005 Springer-Verlag/Wien

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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. https://doi.org/10.1007/3-211-29901-7_7

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  • DOI: https://doi.org/10.1007/3-211-29901-7_7

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-20684-3

  • Online ISBN: 978-3-211-29901-2

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