This article argues that the agent-based computational model permits a distinctive approach to social science for which the term "generative" is suitable. In defending this terminology, features distinguishing the approach from both "inductive" and "deductive" science are given. Then, the following specific contributions to social science are discussed: The agent-based computational model is a new tool for empirical research. It offers a natural environment for the study of connectionist

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... na in social science. Agent-based modeling provides a powerful way to address certain enduring-and especially interdisciplinary-questions. It allows one to subject certain core theories-such as neoclassical microeconomics-to important types of stress (e.g., the effect of evolving preferences). It permits one to study how rules of individual behavior give rise-or "map up"-to macroscopic regularities and organizations. In turn, one can employ laboratory behavioral research findings to select among competing agent-based ("bottom up") models. The agent-based approach may well have the important effect of decoupling individual rationality from macroscopic equilibrium and of separating decision science from social science more generally. Agent-based modeling offers powerful new forms of hybrid theoretical-computational work; these are particularly relevant to the study of non-equilibrium systems. The agentbased approach invites the interpretation of society as a distributed computational device, and in turn the interpretation of social dynamics as a type of computation. This interpretation raises important foundational issues in social science-some related to intractability, and some to undecidability proper. Finally, since "emergence" figures prominently in this literature, I take up the connection between agent-based modeling and classical emergentism, criticizing the latter and arguing that the two are incompatible. ᭧ 1999 John Wiley & Sons, Inc. Key Words: Agent-based models, artificial societies, philosophy of social science 1. GENERATIVE SOCIAL SCIENCE T he agent-based computational model-or artificial society-is a new scientific instrument. 1 It can powerfully advance a distinctive approach to social science, one for which the term "generative" seems appropriate. I will discuss this term more fully below, but in a strong form, the central idea is this: To the generativist, explaining the emergence 2 of macroscopic societal regularities, such as norms or price equilibria, requires that one answer the following question: The Generativist's Question * * How could the decentralized local interactions of heterogeneous autonomous agents generate the given regularity? The agent-based computational model is well-suited to the study of this question since the following features are characteristic 3 : Heterogeneity Representative agent methods-common in macroeconomics-are not used in agent-based models. 4 Nor are agents