Complex systems dynamics: an introduction to automata networks
Complex systems dynamics: an introduction to automata networks
Hidden order: how adaptation builds complexity
Hidden order: how adaptation builds complexity
Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Agent-based modeling and simulation
Winter Simulation Conference
Agent based model of the e-mini future: application for policy making
Proceedings of the Winter Simulation Conference
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Agent-based simulation (ABS) is a relatively recent modeling technique that is being widely used to model complex adaptive systems by many disciplines. Few full length courses exist on agent-based modeling and a standard curriculum has not yet been established, but there is considerable demand to include ABS into simulation courses. Modelers often come to agent-based simulation by way of self-study or attendance at tutorials and short courses. Although there is substantial overlap, there are many aspects of ABS that differ from discrete-event simulation (DES) and System Dynamics (SD), including applicable problem domains, disciplines and backgrounds of students, and the underpinnings of its computational implementation. These factors make ABS difficult to include as an incremental add-on to existing simulation courses. This paper reports on some approaches to teaching the modeling of complex systems and agent-based simulation that the authors have used in a range of classes and workshops.