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Addison-Wesley: Reading, MA.Īxelrod R (1997). The Economy as an Evolving Complex System II, SFI Studies in the Sciences of Complexity. MIT Press: Cambridge, MA.Īrthur WB, Durlauf SN and Lane DA (eds). Mathematical Systems Theory in Biology, Communication, and Finance, IMA Vol. On cellular automaton approaches to modeling biological cells. This process is experimental and the keywords may be updated as the learning algorithm improves.Īlber MS, Kiskowski MA, Glazier JA and Jiang Y (2003). These keywords were added by machine and not by the authors. This article provides a brief introduction to ABMS, illustrates the main concepts and foundations, discusses some recent applications across a variety of disciplines, and identifies methods and toolkits for developing agent models. The development of agent modeling tools, the availability of micro-data, and advances in computation have made possible a growing number of agent-based applications across a variety of domains and disciplines. Agent-based models also include models of behaviour (human or otherwise) and are used to observe the collective effects of agent behaviours and interactions. Such systems often self-organize themselves and create emergent order. Agent-based modeling is a way to model the dynamics of complex systems and complex adaptive systems. Agent-based modeling and simulation (ABMS) is a relatively new approach to modeling systems composed of autonomous, interacting agents.

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