Abstract
Modelling and simulation aim to reproduce the structure and imitate the behavior of real-life systems. For complex dynamic systems, System Dynamics (SD) and Agent-based (AB) modelling are two widely used modelling paradigms that prior to the early 2010’s have traditionally been viewed as mutually exclusive alternatives. This literature review seeks to update the work of Scholl (2001) and Macal, (2010) by providing an overview of attempts to integrate SD and AB over the last ten years. First, the building blocks of both paradigms are presented. Second, their capabilities are contrasted, in order to explore how their integration can yield insights that cannot be generated with one methodology alone. Then, an overview is provided of recent work comparing the outcomes of both paradigms and specifying opportunities for integration. Finally, a critical reflection is presented. The literature review concludes that while paradigm emulation has contributed to expanding the applications of SD, it is the dynamic combination of the two approaches that has become the most promising research line. Integrating SD and AB, and even tools and methods from other disciplines, makes it possible to avoid their individual pitfalls and, hence, to exploit the full potential of their complementary characteristics, so as to provide a more complete representation of complex dynamic systems.
Original language | English |
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Title of host publication | Proceedings of the 34th International Conference of the System Dynamics Society, July 17-21, 2016 Delft, Netherlands |
Publisher | System Dynamics Society |
Number of pages | 13 |
Publication status | Published - 2016 |
Event | 34th international conference of the system dynamics society - Delft, Netherlands Duration: 17 Jul 2016 → 21 Jul 2016 Conference number: 34 |
Conference
Conference | 34th international conference of the system dynamics society |
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Country/Territory | Netherlands |
City | Delft |
Period | 17/07/16 → 21/07/16 |
Keywords
- System Dynamics
- Agent-based modeling
- hybrid models
- Complex dynamic systems
- multi-paradigm approach
- Literature Review