From System Dynamics and Discrete Event to Practical Agent Based Modeling: Reasons, Techniques, Tools Andrei Borshchev and Alexei Filippov. The 22nd International Conference of the System Dynamics Society, July 25 - 29, 2004, Oxford, England

This paper may be considered as a practical reference for those who wish to add (now sufficiently matured) Agent Based modeling to their analysis toolkit and may or may not have some System Dynamics or Discrete Event modeling background. We focus on systems that contain large numbers of active objects (people, business units, animals, vehicles, or even things like projects, stocks, products, etc. that have timing, event ordering or other kind of individual behavior associated with them). We compare the three major paradigms in simulation modeling: System Dynamics, Discrete Event and Agent Based Modeling with respect to how they approach such systems. We show in detail how an Agent Based model can be built from an existing System Dynamics or a Discrete Event model and then show how easily it can be further enhanced to capture much more complicated behavior, dependencies and interactions thus providing for deeper insight in the system being modeled.
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A Methodological Framework for Business-Oriented Modeling of IT Infrastructure Ariel Landau, Segev Wasserkrug, Dagan Gilat, Natalia Razinkov, Aviad Sela, and Sarel Aiber. 2004 Winter Simulation Conference (WSC’04), December 5-8, Washington, D.C., USA

The creation of IT simulation models for uses such as capacity planning and optimization is becoming more and more widespread. Traditionally, the creation of such models required deep modeling and/or programming expertise, thus severely limiting their extensive use. Moreover, many modern intelligent tools now require simulation models in order to carry out their function. For these tools to be widely deployable, the derivation of simulation models must be made possible without requiring excessive technical knowledge.
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