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We live in a dynamic, complex world. Stock prices fluctuate up and down. Tax laws are rewritten to close loopholes. Political candidates and interest groups introduce new issues and concerns and repackage old ones. Yet, paradoxically, our predominant methodological approach characterizes these systems as in equilibrium or as moving between equilibria.

In the past twenty years, that has begun to change with the introduction of agent-based models. Agent-based models consist of dynamically interacting rule-based agents. The systems within which they interact can therefore create complexity like that we see in the real world. These agents are intelligent and purposeful, but they are not so smart as to reach the cognitive closure implied by game theory. The agents in these models situate in space and time. ...

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