Aggregation in agent-based models of economies

Scott E. Page; Scott E. Page

doi:10.1017/S0269888912000112

Abstract: Agent-based models are often described as bottom-up because macro-level phenomena emerge from the micro-level interactions of agents. These macro-level phenomena include fixed points, cycles, dynamic patterns, and long transients. In this paper, I explore the link between micro-level characteristics—learning rules, diversity, network structure, and externalities—and the macro-level patterns they produce. I focus on why we need agent-level modeling, on how these models produce emergent phenomenon, and on how agent-based models help understand outcomes of social systems in a way that differs from the analytic, equilibrium approach.

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Aggregation in agent-based models of economies

Center for the Study of Complex Systems

Corresponding author: Scott E. Page

Published online: 26 April 2012

Abstract: Abstract: Agent-based models are often described as bottom-up because macro-level phenomena emerge from the micro-level interactions of agents. These macro-level phenomena include fixed points, cycles, dynamic patterns, and long transients. In this paper, I explore the link between micro-level characteristics—learning rules, diversity, network structure, and externalities—and the macro-level patterns they produce. I focus on why we need agent-level modeling, on how these models produce emergent phenomenon, and on how agent-based models help understand outcomes of social systems in a way that differs from the analytic, equilibrium approach.

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Acknowledgments

The author acknowledges the National Science Foundation for an IGERT grant and the Army Research Office Grant No. W911NF1010379.

In a more general model, the mapping would depend on time and be denoted by F_t.

See Page (2008) for a survey.

This approach can be used even if a game has a unique equilibrium. Andreoni and Miller (1995) show how even though two auction designs may have the same equilibrium, one may provide a better learning environment. It is equilibrium may be easier to attain given a particular learning rule.

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Scott E. Page. 2012. Aggregation in agent-based models of economies. The Knowledge Engineering Review 27(2)151−162, doi: 10.1017/S0269888912000112

Scott E. Page. 2012. Aggregation in agent-based models of economies. The Knowledge Engineering Review 27(2)151−162, doi: 10.1017/S0269888912000112

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Aggregation in agent-based models of economies

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